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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 21 Dec 2010 14:02:45 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/21/t12929400686xevlkcblcw67y0.htm/, Retrieved Sun, 19 May 2024 17:13:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113583, Retrieved Sun, 19 May 2024 17:13:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-12-05 18:56:24] [b98453cac15ba1066b407e146608df68]
-   PD    [Multiple Regression] [] [2010-12-21 14:02:45] [29eeba0e6ce2cd83aa315a4a7ff8c4aa] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	1	14	41	38	13	12
1	1	18	39	32	16	11
1	1	11	30	35	19	15
1	0	12	31	33	15	6
1	1	16	34	37	14	13
1	1	18	35	29	13	10
1	1	14	39	31	19	12
1	1	14	34	36	15	14
1	1	15	36	35	14	12
1	1	15	37	38	15	9
1	0	17	38	31	16	10
1	1	19	36	34	16	12
1	0	10	38	35	16	12
1	1	16	39	38	16	11
1	1	18	33	37	17	15
1	0	14	32	33	15	12
1	0	14	36	32	15	10
1	1	17	38	38	20	12
1	0	14	39	38	18	11
1	1	16	32	32	16	12
1	0	18	32	33	16	11
1	1	11	31	31	16	12
1	1	14	39	38	19	13
1	1	12	37	39	16	11
1	0	17	39	32	17	12
1	1	9	41	32	17	13
1	0	16	36	35	16	10
1	1	14	33	37	15	14
1	1	15	33	33	16	12
1	0	11	34	33	14	10
1	1	16	31	31	15	12
1	0	13	27	32	12	8
1	1	17	37	31	14	10
1	1	15	34	37	16	12
1	0	14	34	30	14	12
1	0	16	32	33	10	7
1	0	9	29	31	10	9
1	0	15	36	33	14	12
1	1	17	29	31	16	10
1	0	13	35	33	16	10
1	0	15	37	32	16	10
1	1	16	34	33	14	12
1	0	16	38	32	20	15
1	0	12	35	33	14	10
1	1	15	38	28	14	10
1	1	11	37	35	11	12
1	1	15	38	39	14	13
1	1	15	33	34	15	11
1	1	17	36	38	16	11
1	0	13	38	32	14	12
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1	0	14	32	30	14	10
1	0	11	32	33	12	12
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1	0	12	32	32	9	5
1	1	15	37	35	14	6
1	1	16	39	34	16	12
1	1	15	29	34	16	12
1	0	12	37	36	15	11
1	1	12	35	34	16	10
1	0	8	30	28	12	7
1	0	13	38	34	16	12
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1	1	14	31	35	14	11
1	1	15	34	31	16	12
1	0	10	35	37	17	13
1	1	11	36	35	18	14
1	0	12	30	27	18	11
1	1	15	39	40	12	12
1	0	15	35	37	16	12
1	0	14	38	36	10	8
1	1	16	31	38	14	11
1	1	15	34	39	18	14
1	0	15	38	41	18	14
1	0	13	34	27	16	12
1	1	12	39	30	17	9
1	1	17	37	37	16	13
1	1	13	34	31	16	11
1	0	15	28	31	13	12
1	0	13	37	27	16	12
1	0	15	33	36	16	12
1	1	15	35	37	16	12
1	0	16	37	33	15	12
1	1	15	32	34	15	11
1	1	14	33	31	16	10
1	0	15	38	39	14	9
1	1	14	33	34	16	12
1	1	13	29	32	16	12
1	1	7	33	33	15	12
1	1	17	31	36	12	9
1	1	13	36	32	17	15
1	1	15	35	41	16	12
1	1	14	32	28	15	12
1	1	13	29	30	13	12
1	1	16	39	36	16	10
1	1	12	37	35	16	13
1	1	14	35	31	16	9
1	0	17	37	34	16	12
1	0	15	32	36	14	10
1	1	17	38	36	16	14
1	0	12	37	35	16	11
1	1	16	36	37	20	15
1	0	11	32	28	15	11
1	1	15	33	39	16	11
1	0	9	40	32	13	12
1	1	16	38	35	17	12
1	0	15	41	39	16	12
1	0	10	36	35	16	11
1	1	10	43	42	12	7
1	1	15	30	34	16	12
1	1	11	31	33	16	14
1	1	13	32	41	17	11
1	1	18	37	34	12	10
1	0	16	37	32	18	13
1	1	14	33	40	14	13
1	1	14	34	40	14	8
1	1	14	33	35	13	11
1	1	14	38	36	16	12
1	0	12	33	37	13	11
1	1	14	31	27	16	13
1	1	15	38	39	13	12
1	1	15	37	38	16	14
1	1	15	36	31	15	13
1	1	13	31	33	16	15
1	0	17	39	32	15	10
1	1	17	44	39	17	11
1	1	19	33	36	15	9
1	1	15	35	33	12	11
1	0	13	32	33	16	10
1	0	9	28	32	10	11
1	1	15	40	37	16	8
1	0	15	27	30	12	11
1	0	15	37	38	14	12
1	1	16	32	29	15	12
1	0	11	28	22	13	9
1	0	14	34	35	15	11
1	1	11	30	35	11	10
1	1	15	35	34	12	8
1	0	13	31	35	11	9
1	1	15	32	34	16	8
1	0	16	30	37	15	9
1	1	14	30	35	17	15
1	0	15	31	23	16	11
1	1	16	40	31	10	8
1	1	16	32	27	18	13
1	0	11	36	36	13	12
1	0	12	32	31	16	12
1	0	9	35	32	13	9
1	1	16	38	39	10	7
1	1	13	42	37	15	13
1	0	16	34	38	16	9
1	1	12	35	39	16	6
1	1	9	38	34	14	8
1	1	13	33	31	10	8
1	1	14	32	37	13	6
1	1	19	33	36	15	9
1	1	13	34	32	16	11
1	1	12	32	38	12	8
0	0	10	27	26	13	10
0	0	14	31	26	12	8
0	0	16	38	33	17	14
0	1	10	34	39	15	10
0	0	11	24	30	10	8
0	0	14	30	33	14	11
0	1	12	26	25	11	12
0	1	9	34	38	13	12
0	0	9	27	37	16	12
0	0	11	37	31	12	5
0	1	16	36	37	16	12
0	0	9	41	35	12	10
0	1	13	29	25	9	7
0	1	16	36	28	12	12
0	0	13	32	35	15	11
0	1	9	37	33	12	8
0	0	12	30	30	12	9
0	1	16	31	31	14	10
0	1	11	38	37	12	9
0	1	14	36	36	16	12
0	0	13	35	30	11	6
0	0	15	31	36	19	15
0	0	14	38	32	15	12
0	1	16	22	28	8	12
0	1	13	32	36	16	12
0	0	14	36	34	17	11
0	1	15	39	31	12	7
0	0	13	28	28	11	7
0	0	11	32	36	11	5
0	1	11	32	36	14	12
0	1	14	38	40	16	12
0	1	15	32	33	12	3
0	1	11	35	37	16	11
0	1	15	32	32	13	10
0	0	12	37	38	15	12
0	1	14	34	31	16	9
0	1	14	33	37	16	12
0	0	8	33	33	14	9
0	0	9	30	30	16	12
0	0	15	24	30	14	10
0	0	17	34	31	11	9
0	0	13	34	32	12	12
0	1	15	33	34	15	8
0	1	15	34	36	15	11
0	1	14	35	37	16	11
0	0	16	35	36	16	12
0	0	13	36	33	11	10
0	0	16	34	33	15	10
0	1	9	34	33	12	12
0	0	16	41	44	12	12
0	0	11	32	39	15	11
0	0	10	30	32	15	8
0	1	11	35	35	16	12
0	0	15	28	25	14	10
0	1	17	33	35	17	11
0	1	14	39	34	14	10
0	0	8	36	35	13	8
0	1	15	36	39	15	12
0	0	11	35	33	13	12
0	0	16	38	36	14	10
0	1	10	33	32	15	12
0	0	15	31	32	12	9
0	1	16	32	36	8	6
0	0	19	31	32	14	10
0	0	12	33	34	14	9
0	0	8	34	33	11	9
0	0	11	34	35	12	9
0	1	14	34	30	13	6
0	0	9	33	38	10	10
0	0	15	32	34	16	6
0	1	13	41	33	18	14
0	1	16	34	32	13	10
0	0	11	36	31	11	10
0	0	12	37	30	4	6
0	0	13	36	27	13	12
0	1	10	29	31	16	12
0	0	11	37	30	10	7
0	0	12	27	32	12	8
0	0	8	35	35	12	11
0	0	12	28	28	10	3
0	0	12	35	33	13	6
0	0	11	29	35	12	8
0	0	13	32	35	14	9
0	1	14	36	32	10	9
0	1	10	19	21	12	8
0	1	12	21	20	12	9
0	0	15	31	34	11	7
0	0	13	33	32	10	7
0	1	13	36	34	12	6
0	1	13	33	32	16	9
0	0	12	37	33	12	10
0	0	12	34	33	14	11
0	0	9	35	37	16	12
0	1	9	31	32	14	8
0	1	15	37	34	13	11
0	1	10	35	30	4	3
0	1	14	27	30	15	11
0	0	15	34	38	11	12
0	0	7	40	36	11	7
0	0	14	29	32	14	9
0	0	8	38	34	15	12
0	1	10	34	33	14	8
0	0	13	21	27	13	11
0	0	13	36	32	11	8
0	1	13	38	34	15	10
0	0	8	30	29	11	8
0	0	12	35	35	13	7
0	1	13	30	27	13	8
0	1	12	36	33	16	10
0	0	10	34	38	13	8
0	1	13	35	36	16	12
0	0	12	34	33	16	14
0	0	9	32	39	12	7
0	1	15	33	29	7	6
0	0	13	33	32	16	11
0	1	13	26	34	5	4
0	0	13	35	38	16	9
0	0	15	21	17	4	5
0	0	15	38	35	12	9
0	0	14	35	32	15	11
0	1	15	33	34	14	12
0	0	11	37	36	11	9
0	0	15	38	31	16	12
0	1	14	34	35	15	10
0	0	13	27	29	12	9
0	1	12	16	22	6	6
0	0	16	40	41	16	10
0	0	16	36	36	10	9
0	1	9	42	42	15	13
0	1	14	30	33	14	12

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 13 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113583&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113583&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113583&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Multiple Linear Regression - Estimated Regression Equation
Separate[t] = + 14.7798585054866 -0.0486161950838779Populatie[t] + 0.700533423699235Geslacht[t] -0.0308352531395231Happiness[t] + 0.460644654108866Connected[t] + 0.169100541942854Learning[t] + 0.0831719663977894Software[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Separate[t] =  +  14.7798585054866 -0.0486161950838779Populatie[t] +  0.700533423699235Geslacht[t] -0.0308352531395231Happiness[t] +  0.460644654108866Connected[t] +  0.169100541942854Learning[t] +  0.0831719663977894Software[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113583&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Separate[t] =  +  14.7798585054866 -0.0486161950838779Populatie[t] +  0.700533423699235Geslacht[t] -0.0308352531395231Happiness[t] +  0.460644654108866Connected[t] +  0.169100541942854Learning[t] +  0.0831719663977894Software[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113583&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113583&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
Separate[t] = + 14.7798585054866 -0.0486161950838779Populatie[t] + 0.700533423699235Geslacht[t] -0.0308352531395231Happiness[t] + 0.460644654108866Connected[t] + 0.169100541942854Learning[t] + 0.0831719663977894Software[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)14.77985850548661.9800487.464400
Populatie-0.04861619508387790.435544-0.11160.9112030.455601
Geslacht0.7005334236992350.4040091.7340.0840230.042012
Happiness-0.03083525313952310.08281-0.37240.7099050.354953
Connected0.4606446541088660.0503879.142100
Learning0.1691005419428540.1028081.64480.1011260.050563
Software0.08317196639778940.1101260.75520.4507360.225368

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 14.7798585054866 & 1.980048 & 7.4644 & 0 & 0 \tabularnewline
Populatie & -0.0486161950838779 & 0.435544 & -0.1116 & 0.911203 & 0.455601 \tabularnewline
Geslacht & 0.700533423699235 & 0.404009 & 1.734 & 0.084023 & 0.042012 \tabularnewline
Happiness & -0.0308352531395231 & 0.08281 & -0.3724 & 0.709905 & 0.354953 \tabularnewline
Connected & 0.460644654108866 & 0.050387 & 9.1421 & 0 & 0 \tabularnewline
Learning & 0.169100541942854 & 0.102808 & 1.6448 & 0.101126 & 0.050563 \tabularnewline
Software & 0.0831719663977894 & 0.110126 & 0.7552 & 0.450736 & 0.225368 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113583&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]14.7798585054866[/C][C]1.980048[/C][C]7.4644[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Populatie[/C][C]-0.0486161950838779[/C][C]0.435544[/C][C]-0.1116[/C][C]0.911203[/C][C]0.455601[/C][/ROW]
[ROW][C]Geslacht[/C][C]0.700533423699235[/C][C]0.404009[/C][C]1.734[/C][C]0.084023[/C][C]0.042012[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.0308352531395231[/C][C]0.08281[/C][C]-0.3724[/C][C]0.709905[/C][C]0.354953[/C][/ROW]
[ROW][C]Connected[/C][C]0.460644654108866[/C][C]0.050387[/C][C]9.1421[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Learning[/C][C]0.169100541942854[/C][C]0.102808[/C][C]1.6448[/C][C]0.101126[/C][C]0.050563[/C][/ROW]
[ROW][C]Software[/C][C]0.0831719663977894[/C][C]0.110126[/C][C]0.7552[/C][C]0.450736[/C][C]0.225368[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113583&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113583&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)14.77985850548661.9800487.464400
Populatie-0.04861619508387790.435544-0.11160.9112030.455601
Geslacht0.7005334236992350.4040091.7340.0840230.042012
Happiness-0.03083525313952310.08281-0.37240.7099050.354953
Connected0.4606446541088660.0503879.142100
Learning0.1691005419428540.1028081.64480.1011260.050563
Software0.08317196639778940.1101260.75520.4507360.225368






Multiple Linear Regression - Regression Statistics
Multiple R0.553216177627319
R-squared0.306048139188582
Adjusted R-squared0.291230661733534
F-TEST (value)20.6545371921127
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.28868462732981
Sum Squared Residuals3039.14048842796

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.553216177627319 \tabularnewline
R-squared & 0.306048139188582 \tabularnewline
Adjusted R-squared & 0.291230661733534 \tabularnewline
F-TEST (value) & 20.6545371921127 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 281 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.28868462732981 \tabularnewline
Sum Squared Residuals & 3039.14048842796 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113583&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.553216177627319[/C][/ROW]
[ROW][C]R-squared[/C][C]0.306048139188582[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.291230661733534[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]20.6545371921127[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]281[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.28868462732981[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3039.14048842796[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113583&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113583&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.553216177627319
R-squared0.306048139188582
Adjusted R-squared0.291230661733534
F-TEST (value)20.6545371921127
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.28868462732981
Sum Squared Residuals3039.14048842796






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
13837.08288365064270.917116349357299
23236.4623829892977-4.46238298929768
33533.37241736571431.62758263428573
43331.67674347763291.32325652236714
53734.04897307394232.95102692605774
62934.0293307806359-5.02933078063587
73137.1761975940821-6.17619759408213
83634.36291608856201.63708391143804
93534.91792566890170.082074331098265
103835.29815496576012.70184503423991
113135.2488681982313-4.24886819823132
123435.1327857402294-1.13278574022935
133535.6310589030036-0.631058903003556
143836.52405349557671.47594650442327
153734.20030347217852.7996965278215
163332.57474942384940.425250576150586
173234.2509841074893-2.2509841074893
183836.79214772249751.20785227750245
193836.22339166204221.77660833795775
203233.3827128832125-1.38271288321246
213332.53733698683640.462663013163614
223133.0762444948012-2.07624449480121
233837.25936956047990.740630439520082
243935.72610519991713.27389480008291
253236.0449573270786-4.04495732707861
263237.9966340505096-5.99663405050956
273534.35841414315310.641585856846894
283733.90227143445313.09772856554691
293333.8741927904608-0.874192790460846
303333.2531000167473-0.253100016747282
313132.7529676871607-1.75296768716074
323229.46237191502492.53762808497511
333135.150555883936-4.15055588393598
343734.33483744456972.66516255543029
353033.3269381901243-3.32693819012429
363331.25171637586721.74828362413285
373130.25197311831280.748026881687208
383334.2173922452025-1.2173922452025
393131.8035997349508-0.803599734950756
403333.9902752484628-0.99027524846281
413234.8498940504015-2.84989405040150
423333.9658011075445-0.96580110754448
433236.3719654511312-4.3719654511312
443333.6829094177166-0.682909417716625
452835.6728710443239-7.67287104432389
463534.99460970974010.00539029025986888
473935.92238694351733.07761305648274
483433.62192028212020.378079717879798
493835.11128428011062.88871571988939
503235.2003520596993-3.20035205969928
513833.5490568160084.45094318399196
523032.239304949111-2.23930494911098
533332.15995355743940.84004644256058
543834.51051517038613.48948482961393
553231.03961291368680.960387086313191
563534.87953852462390.120461475376136
573436.6072254619745-2.60722546197452
583432.03161417402541.96838582597462
593634.8564712342751.143528765725
603434.7216439253016-0.721643925301568
612830.9153101766513-2.91531017665131
623435.538553143585-1.53855314358499
633534.62452238992340.375477610076617
643532.56236568509912.43763431490086
653134.3348374445697-3.33483744456971
663734.50139744901762.4986025509824
673535.8840127820268-0.884012782026823
682732.1392602813415-5.1392602813415
694035.96165854734264.03834145265737
703734.09494867497932.90505132502066
713634.16042677319721.83957322680282
723832.50069517882015.49930482117991
733934.8393824612514.160617538749
744135.98142765398725.01857234601277
752733.6959745271495-6.69597452714952
763036.6501511172821-6.6501511172821
773735.73827286701511.26172713298495
783134.313335984451-3.31333598445097
793130.36313447038870.636865529611282
802735.0779084894761-8.07790848947612
813633.17365936676162.82634063323839
823734.79548209867862.20451790132142
833334.8163021881147-1.81630218811470
843433.16127562801130.838724371988664
853133.7386841108048-2.73868411080479
863934.88916565422694.11083434577313
873433.90502804360040.0949719563996314
883232.0932846803044-0.0932846803044281
893333.9517742736342-0.951774273634176
903631.96531490899934.03468509100072
913235.7364137002027-3.73641370020271
924134.79548209867866.20451790132142
932833.2752828475487-5.27528284754865
943031.5859830544759-1.58598305447586
953636.4408815291789-0.440881529178940
963535.8924491327127-0.892449132712668
973134.5768014526247-3.57680145262473
983434.954567476918-0.954567476918028
993632.20846969597153.79153030402854
1003636.2820894875217-0.282089487521708
1013535.0255717762179-0.0255717762178542
1023736.15120956661270.848790433387295
1032832.5840832168702-4.58408321687020
1043933.79102082406315.20897917593694
1053236.0758818385322-4.07588183853225
1063536.3156813498085-1.31568134980851
1073936.85881659963252.14118340036746
1083534.6265976283880.373402371611966
1094237.54255359748684.45744640251324
1103432.49225882813421.50774117186575
1113333.2425884275968-0.242588427596785
1124133.56114721817617.43885278182391
1133434.7815195469107-0.781519546910745
1143235.4067757803411-3.40677578034105
1154033.64999892611256.35000107388755
1164033.69478374823246.30521625176763
1173533.3145544513741.68544554862598
1183636.2082513141447-0.208251314144699
1193732.67569153395384.32430846604617
1202733.0669107017804-6.06691070178043
1213935.67011443517663.32988556482339
1223835.88311533969192.11688466030811
1233135.1701981772424-4.17019817724238
1243333.2640898877155-0.264089887715528
1253235.5404123103973-3.54041231039733
1263938.96554205492440.0344579450756088
1273633.33223533676652.66776466323347
1283334.0359079645094-1.03590796450937
1293332.60834128613620.391658713863788
1303229.95767239699952.04232760300050
1313736.76601750363180.23398249636825
1323029.65021730793920.349782692060791
1333834.67803689931143.32196310068863
1342933.2136123412696-4.2136123412696
1352230.2369595837534-8.23695958375344
1363533.41286676566941.58713323433064
1373531.60375319818253.39624680181751
1383433.7863920653160.213607934683997
1393531.21902195591533.78097804408471
1403433.08086027076080.919139729239178
1413731.34227371015935.65772628984073
1423532.941710522412.05828947759001
1432332.1691980921461-9.16919809214609
1443135.7205789988351-4.7205789988351
1452733.8040859334960-6.80408593349595
1463634.17163271581771.82836728418226
1473132.8055204720713-1.80552047207131
1483233.5231426687945-1.52314266879455
1493934.71611772421964.28388227578042
1503737.9957366081746-0.995736608174622
1513833.35395286853764.64604713146241
1523934.38895605971044.61104394028959
1533435.6915386303655-1.69153863036545
1543132.5885721794916-1.58857217949161
1553732.43804996527624.56195003472379
1563633.33223533676652.66776466323347
1573234.313335984451-2.31333598445097
1583832.4969638624085.50303613759202
1592629.9389383442658-3.93893834426577
1602631.3227314734047-5.32273147340471
1613335.8301080539887-2.83010805398873
1623934.20218543061284.79781456938723
1633027.85252357017552.14747642982449
1643331.44980380237491.55019619762508
1652529.9452994564870-4.94529945648696
1663834.06116353266223.93883646733783
1673730.64341915602946.35658084397057
1683133.9295892582831-2.9295892582831
1693735.27390769473181.7260923052682
1703536.2496982129866-1.24969821298656
1712530.5423372497994-5.54233724979938
1722834.5975055269604-6.59750552696038
1733532.5710289056752.42897109432497
1743334.9413090874548-1.94130908745475
1753031.0069292919727-1.00692929197268
1763132.4661394075062-1.46613940750618
1773735.42345520168241.57654479831764
1783635.33557820101080.664421798989156
1793032.8607008682413-2.86070086824126
1803633.05780377864972.94219622135031
1813235.3872335435865-3.38723354358649
1822827.47207820166480.527921798335158
1833633.52383483771492.47616516228510
1843434.7209733528567-0.720973352856674
1853135.5944149104376-4.59441491043756
1862829.719360255877-1.71936025587699
1873631.45726544579594.54273455420408
1883633.24730426010822.75269573989176
1894036.25686750922863.74313249077142
1903332.03721446608430.962785533915664
1913734.88426733992282.11573266007724
1923232.7885187728117-0.788518772811717
1933834.98825939575673.01174060424333
1943134.1647729935997-3.16477299359974
1953733.95364423868423.04635576131575
1963332.85040535074310.149594649256926
1973032.025353118356-2.02535311835603
1983028.57192865818441.42807134181559
1993132.5262311007677-1.52623110076767
2003233.068188554462-1.06818855446198
2013433.42102057801070.578979421989288
2023634.13118113131291.86881886868705
2033734.79176158050422.20823841949581
2043634.11272961692371.88727038307630
2053333.6540333879413-0.654033387941283
2063333.3166404880764-0.316640488076399
2073333.8920629907193-0.892062990719312
2084436.20019537380557.79980462619453
2093932.63269941195416.36730058804593
2103231.49272945768250.507270542317505
2113534.96743930632050.0325606936794515
2122530.4145072746199-5.41450727461987
2133533.94706705481071.05293294518926
2143436.2129671466562-2.21296714665616
2153533.9800668047291.01993319527097
2163935.13564240592853.86435759407153
2173333.7596042567927-0.75960425679275
2183634.9901185625691.00988143743099
2193233.9078847092995-1.90788470929949
2203231.3750681866630.624931813337028
2213631.57949294436684.42050705563324
2223231.67310022438840.326899775611623
2233432.7270643381851.27293566181502
2243332.80374837902340.196251620976623
2253532.88034316154772.11965683845234
2263033.4079554685778-3.40795546857781
2273832.22633989622995.77366010377008
2283432.26259910934991.73740089065011
2293338.174181741376-5.17418174137598
2303233.6789728278899-1.67897282788993
2313133.7157038942203-2.71570389422033
2323032.6291216359985-2.62912163599854
2332734.1585784046226-7.15857840462257
2343132.2344066348069-1.23440663480688
2353033.757732107193-3.75773210719297
2363229.54182336324832.45817663675171
2373533.59983750787071.40016249212932
2382829.2484071014825-1.2484071014825
2393333.2297372052665-0.229737205266491
2403530.49394792460554.50605207539446
2413532.23558443093662.76441556906341
2423234.0714590501603-2.07145905016035
2432126.6188700603556-5.61887006035564
2442027.5616608286921-7.56166082869212
2453431.03962371192452.96037628807546
2463231.85348298447850.146517015521537
2473434.1909794879922-0.190979487992215
2483233.7349635926304-1.7349635926304
2493334.3146138371325-1.31461383713253
2503333.3540529250894-0.354052925089426
2513734.32857638890042.67142361109964
2523232.5156422466873-0.515642246687265
2533435.1749140097538-1.17491400975384
2543032.2205203585657-2.22052035856572
2553030.9375038056904-0.937503805690408
2563832.83741750624015.16258249375992
2573635.43210762402050.567892375979483
2583230.82281521547051.17718478452953
2593435.5722450624236-1.57224506242363
2603333.8667409558743-0.86674095587434
2612727.1657366265918-0.165736626591792
2623233.4876894551457-1.48768945514570
2633435.9522582876297-1.95225828762967
2642930.8779977961901-1.87799779619012
2653533.31290917166431.68709082833572
2662731.7625560380775-4.76255603807745
2673335.2309047744943-2.23090477449431
2683832.99710699023235.00289300976775
2693634.90576880004151.09423119995850
2703333.9417699081685-0.941769908168503
2713931.85438042681347.1456195731866
2722931.9018723096723-2.9018723096723
2733233.2007741017267-1.20077410172675
2743428.2344852205085.765514779492
2753833.95571947714894.0442805228511
2761725.0831294444403-8.08312944444032
2773534.5995807654250.400419234574966
2783233.9221276148621-1.9221276148621
2793433.5846079016590.415392098340985
2803634.09317658193141.90682341806859
2813135.5254988323898-4.52549883238982
2823534.07884441805470.92115558194532
2832929.5941600765066-0.594160076506555
2842223.9943184072973-1.99431840729729
2854136.24960895467244.75039104532755
2863633.30925512018212.69074487981793
2874238.16769381581663.83230618418341
2883332.23350919247190.766490807528059

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 38 & 37.0828836506427 & 0.917116349357299 \tabularnewline
2 & 32 & 36.4623829892977 & -4.46238298929768 \tabularnewline
3 & 35 & 33.3724173657143 & 1.62758263428573 \tabularnewline
4 & 33 & 31.6767434776329 & 1.32325652236714 \tabularnewline
5 & 37 & 34.0489730739423 & 2.95102692605774 \tabularnewline
6 & 29 & 34.0293307806359 & -5.02933078063587 \tabularnewline
7 & 31 & 37.1761975940821 & -6.17619759408213 \tabularnewline
8 & 36 & 34.3629160885620 & 1.63708391143804 \tabularnewline
9 & 35 & 34.9179256689017 & 0.082074331098265 \tabularnewline
10 & 38 & 35.2981549657601 & 2.70184503423991 \tabularnewline
11 & 31 & 35.2488681982313 & -4.24886819823132 \tabularnewline
12 & 34 & 35.1327857402294 & -1.13278574022935 \tabularnewline
13 & 35 & 35.6310589030036 & -0.631058903003556 \tabularnewline
14 & 38 & 36.5240534955767 & 1.47594650442327 \tabularnewline
15 & 37 & 34.2003034721785 & 2.7996965278215 \tabularnewline
16 & 33 & 32.5747494238494 & 0.425250576150586 \tabularnewline
17 & 32 & 34.2509841074893 & -2.2509841074893 \tabularnewline
18 & 38 & 36.7921477224975 & 1.20785227750245 \tabularnewline
19 & 38 & 36.2233916620422 & 1.77660833795775 \tabularnewline
20 & 32 & 33.3827128832125 & -1.38271288321246 \tabularnewline
21 & 33 & 32.5373369868364 & 0.462663013163614 \tabularnewline
22 & 31 & 33.0762444948012 & -2.07624449480121 \tabularnewline
23 & 38 & 37.2593695604799 & 0.740630439520082 \tabularnewline
24 & 39 & 35.7261051999171 & 3.27389480008291 \tabularnewline
25 & 32 & 36.0449573270786 & -4.04495732707861 \tabularnewline
26 & 32 & 37.9966340505096 & -5.99663405050956 \tabularnewline
27 & 35 & 34.3584141431531 & 0.641585856846894 \tabularnewline
28 & 37 & 33.9022714344531 & 3.09772856554691 \tabularnewline
29 & 33 & 33.8741927904608 & -0.874192790460846 \tabularnewline
30 & 33 & 33.2531000167473 & -0.253100016747282 \tabularnewline
31 & 31 & 32.7529676871607 & -1.75296768716074 \tabularnewline
32 & 32 & 29.4623719150249 & 2.53762808497511 \tabularnewline
33 & 31 & 35.150555883936 & -4.15055588393598 \tabularnewline
34 & 37 & 34.3348374445697 & 2.66516255543029 \tabularnewline
35 & 30 & 33.3269381901243 & -3.32693819012429 \tabularnewline
36 & 33 & 31.2517163758672 & 1.74828362413285 \tabularnewline
37 & 31 & 30.2519731183128 & 0.748026881687208 \tabularnewline
38 & 33 & 34.2173922452025 & -1.2173922452025 \tabularnewline
39 & 31 & 31.8035997349508 & -0.803599734950756 \tabularnewline
40 & 33 & 33.9902752484628 & -0.99027524846281 \tabularnewline
41 & 32 & 34.8498940504015 & -2.84989405040150 \tabularnewline
42 & 33 & 33.9658011075445 & -0.96580110754448 \tabularnewline
43 & 32 & 36.3719654511312 & -4.3719654511312 \tabularnewline
44 & 33 & 33.6829094177166 & -0.682909417716625 \tabularnewline
45 & 28 & 35.6728710443239 & -7.67287104432389 \tabularnewline
46 & 35 & 34.9946097097401 & 0.00539029025986888 \tabularnewline
47 & 39 & 35.9223869435173 & 3.07761305648274 \tabularnewline
48 & 34 & 33.6219202821202 & 0.378079717879798 \tabularnewline
49 & 38 & 35.1112842801106 & 2.88871571988939 \tabularnewline
50 & 32 & 35.2003520596993 & -3.20035205969928 \tabularnewline
51 & 38 & 33.549056816008 & 4.45094318399196 \tabularnewline
52 & 30 & 32.239304949111 & -2.23930494911098 \tabularnewline
53 & 33 & 32.1599535574394 & 0.84004644256058 \tabularnewline
54 & 38 & 34.5105151703861 & 3.48948482961393 \tabularnewline
55 & 32 & 31.0396129136868 & 0.960387086313191 \tabularnewline
56 & 35 & 34.8795385246239 & 0.120461475376136 \tabularnewline
57 & 34 & 36.6072254619745 & -2.60722546197452 \tabularnewline
58 & 34 & 32.0316141740254 & 1.96838582597462 \tabularnewline
59 & 36 & 34.856471234275 & 1.143528765725 \tabularnewline
60 & 34 & 34.7216439253016 & -0.721643925301568 \tabularnewline
61 & 28 & 30.9153101766513 & -2.91531017665131 \tabularnewline
62 & 34 & 35.538553143585 & -1.53855314358499 \tabularnewline
63 & 35 & 34.6245223899234 & 0.375477610076617 \tabularnewline
64 & 35 & 32.5623656850991 & 2.43763431490086 \tabularnewline
65 & 31 & 34.3348374445697 & -3.33483744456971 \tabularnewline
66 & 37 & 34.5013974490176 & 2.4986025509824 \tabularnewline
67 & 35 & 35.8840127820268 & -0.884012782026823 \tabularnewline
68 & 27 & 32.1392602813415 & -5.1392602813415 \tabularnewline
69 & 40 & 35.9616585473426 & 4.03834145265737 \tabularnewline
70 & 37 & 34.0949486749793 & 2.90505132502066 \tabularnewline
71 & 36 & 34.1604267731972 & 1.83957322680282 \tabularnewline
72 & 38 & 32.5006951788201 & 5.49930482117991 \tabularnewline
73 & 39 & 34.839382461251 & 4.160617538749 \tabularnewline
74 & 41 & 35.9814276539872 & 5.01857234601277 \tabularnewline
75 & 27 & 33.6959745271495 & -6.69597452714952 \tabularnewline
76 & 30 & 36.6501511172821 & -6.6501511172821 \tabularnewline
77 & 37 & 35.7382728670151 & 1.26172713298495 \tabularnewline
78 & 31 & 34.313335984451 & -3.31333598445097 \tabularnewline
79 & 31 & 30.3631344703887 & 0.636865529611282 \tabularnewline
80 & 27 & 35.0779084894761 & -8.07790848947612 \tabularnewline
81 & 36 & 33.1736593667616 & 2.82634063323839 \tabularnewline
82 & 37 & 34.7954820986786 & 2.20451790132142 \tabularnewline
83 & 33 & 34.8163021881147 & -1.81630218811470 \tabularnewline
84 & 34 & 33.1612756280113 & 0.838724371988664 \tabularnewline
85 & 31 & 33.7386841108048 & -2.73868411080479 \tabularnewline
86 & 39 & 34.8891656542269 & 4.11083434577313 \tabularnewline
87 & 34 & 33.9050280436004 & 0.0949719563996314 \tabularnewline
88 & 32 & 32.0932846803044 & -0.0932846803044281 \tabularnewline
89 & 33 & 33.9517742736342 & -0.951774273634176 \tabularnewline
90 & 36 & 31.9653149089993 & 4.03468509100072 \tabularnewline
91 & 32 & 35.7364137002027 & -3.73641370020271 \tabularnewline
92 & 41 & 34.7954820986786 & 6.20451790132142 \tabularnewline
93 & 28 & 33.2752828475487 & -5.27528284754865 \tabularnewline
94 & 30 & 31.5859830544759 & -1.58598305447586 \tabularnewline
95 & 36 & 36.4408815291789 & -0.440881529178940 \tabularnewline
96 & 35 & 35.8924491327127 & -0.892449132712668 \tabularnewline
97 & 31 & 34.5768014526247 & -3.57680145262473 \tabularnewline
98 & 34 & 34.954567476918 & -0.954567476918028 \tabularnewline
99 & 36 & 32.2084696959715 & 3.79153030402854 \tabularnewline
100 & 36 & 36.2820894875217 & -0.282089487521708 \tabularnewline
101 & 35 & 35.0255717762179 & -0.0255717762178542 \tabularnewline
102 & 37 & 36.1512095666127 & 0.848790433387295 \tabularnewline
103 & 28 & 32.5840832168702 & -4.58408321687020 \tabularnewline
104 & 39 & 33.7910208240631 & 5.20897917593694 \tabularnewline
105 & 32 & 36.0758818385322 & -4.07588183853225 \tabularnewline
106 & 35 & 36.3156813498085 & -1.31568134980851 \tabularnewline
107 & 39 & 36.8588165996325 & 2.14118340036746 \tabularnewline
108 & 35 & 34.626597628388 & 0.373402371611966 \tabularnewline
109 & 42 & 37.5425535974868 & 4.45744640251324 \tabularnewline
110 & 34 & 32.4922588281342 & 1.50774117186575 \tabularnewline
111 & 33 & 33.2425884275968 & -0.242588427596785 \tabularnewline
112 & 41 & 33.5611472181761 & 7.43885278182391 \tabularnewline
113 & 34 & 34.7815195469107 & -0.781519546910745 \tabularnewline
114 & 32 & 35.4067757803411 & -3.40677578034105 \tabularnewline
115 & 40 & 33.6499989261125 & 6.35000107388755 \tabularnewline
116 & 40 & 33.6947837482324 & 6.30521625176763 \tabularnewline
117 & 35 & 33.314554451374 & 1.68544554862598 \tabularnewline
118 & 36 & 36.2082513141447 & -0.208251314144699 \tabularnewline
119 & 37 & 32.6756915339538 & 4.32430846604617 \tabularnewline
120 & 27 & 33.0669107017804 & -6.06691070178043 \tabularnewline
121 & 39 & 35.6701144351766 & 3.32988556482339 \tabularnewline
122 & 38 & 35.8831153396919 & 2.11688466030811 \tabularnewline
123 & 31 & 35.1701981772424 & -4.17019817724238 \tabularnewline
124 & 33 & 33.2640898877155 & -0.264089887715528 \tabularnewline
125 & 32 & 35.5404123103973 & -3.54041231039733 \tabularnewline
126 & 39 & 38.9655420549244 & 0.0344579450756088 \tabularnewline
127 & 36 & 33.3322353367665 & 2.66776466323347 \tabularnewline
128 & 33 & 34.0359079645094 & -1.03590796450937 \tabularnewline
129 & 33 & 32.6083412861362 & 0.391658713863788 \tabularnewline
130 & 32 & 29.9576723969995 & 2.04232760300050 \tabularnewline
131 & 37 & 36.7660175036318 & 0.23398249636825 \tabularnewline
132 & 30 & 29.6502173079392 & 0.349782692060791 \tabularnewline
133 & 38 & 34.6780368993114 & 3.32196310068863 \tabularnewline
134 & 29 & 33.2136123412696 & -4.2136123412696 \tabularnewline
135 & 22 & 30.2369595837534 & -8.23695958375344 \tabularnewline
136 & 35 & 33.4128667656694 & 1.58713323433064 \tabularnewline
137 & 35 & 31.6037531981825 & 3.39624680181751 \tabularnewline
138 & 34 & 33.786392065316 & 0.213607934683997 \tabularnewline
139 & 35 & 31.2190219559153 & 3.78097804408471 \tabularnewline
140 & 34 & 33.0808602707608 & 0.919139729239178 \tabularnewline
141 & 37 & 31.3422737101593 & 5.65772628984073 \tabularnewline
142 & 35 & 32.94171052241 & 2.05828947759001 \tabularnewline
143 & 23 & 32.1691980921461 & -9.16919809214609 \tabularnewline
144 & 31 & 35.7205789988351 & -4.7205789988351 \tabularnewline
145 & 27 & 33.8040859334960 & -6.80408593349595 \tabularnewline
146 & 36 & 34.1716327158177 & 1.82836728418226 \tabularnewline
147 & 31 & 32.8055204720713 & -1.80552047207131 \tabularnewline
148 & 32 & 33.5231426687945 & -1.52314266879455 \tabularnewline
149 & 39 & 34.7161177242196 & 4.28388227578042 \tabularnewline
150 & 37 & 37.9957366081746 & -0.995736608174622 \tabularnewline
151 & 38 & 33.3539528685376 & 4.64604713146241 \tabularnewline
152 & 39 & 34.3889560597104 & 4.61104394028959 \tabularnewline
153 & 34 & 35.6915386303655 & -1.69153863036545 \tabularnewline
154 & 31 & 32.5885721794916 & -1.58857217949161 \tabularnewline
155 & 37 & 32.4380499652762 & 4.56195003472379 \tabularnewline
156 & 36 & 33.3322353367665 & 2.66776466323347 \tabularnewline
157 & 32 & 34.313335984451 & -2.31333598445097 \tabularnewline
158 & 38 & 32.496963862408 & 5.50303613759202 \tabularnewline
159 & 26 & 29.9389383442658 & -3.93893834426577 \tabularnewline
160 & 26 & 31.3227314734047 & -5.32273147340471 \tabularnewline
161 & 33 & 35.8301080539887 & -2.83010805398873 \tabularnewline
162 & 39 & 34.2021854306128 & 4.79781456938723 \tabularnewline
163 & 30 & 27.8525235701755 & 2.14747642982449 \tabularnewline
164 & 33 & 31.4498038023749 & 1.55019619762508 \tabularnewline
165 & 25 & 29.9452994564870 & -4.94529945648696 \tabularnewline
166 & 38 & 34.0611635326622 & 3.93883646733783 \tabularnewline
167 & 37 & 30.6434191560294 & 6.35658084397057 \tabularnewline
168 & 31 & 33.9295892582831 & -2.9295892582831 \tabularnewline
169 & 37 & 35.2739076947318 & 1.7260923052682 \tabularnewline
170 & 35 & 36.2496982129866 & -1.24969821298656 \tabularnewline
171 & 25 & 30.5423372497994 & -5.54233724979938 \tabularnewline
172 & 28 & 34.5975055269604 & -6.59750552696038 \tabularnewline
173 & 35 & 32.571028905675 & 2.42897109432497 \tabularnewline
174 & 33 & 34.9413090874548 & -1.94130908745475 \tabularnewline
175 & 30 & 31.0069292919727 & -1.00692929197268 \tabularnewline
176 & 31 & 32.4661394075062 & -1.46613940750618 \tabularnewline
177 & 37 & 35.4234552016824 & 1.57654479831764 \tabularnewline
178 & 36 & 35.3355782010108 & 0.664421798989156 \tabularnewline
179 & 30 & 32.8607008682413 & -2.86070086824126 \tabularnewline
180 & 36 & 33.0578037786497 & 2.94219622135031 \tabularnewline
181 & 32 & 35.3872335435865 & -3.38723354358649 \tabularnewline
182 & 28 & 27.4720782016648 & 0.527921798335158 \tabularnewline
183 & 36 & 33.5238348377149 & 2.47616516228510 \tabularnewline
184 & 34 & 34.7209733528567 & -0.720973352856674 \tabularnewline
185 & 31 & 35.5944149104376 & -4.59441491043756 \tabularnewline
186 & 28 & 29.719360255877 & -1.71936025587699 \tabularnewline
187 & 36 & 31.4572654457959 & 4.54273455420408 \tabularnewline
188 & 36 & 33.2473042601082 & 2.75269573989176 \tabularnewline
189 & 40 & 36.2568675092286 & 3.74313249077142 \tabularnewline
190 & 33 & 32.0372144660843 & 0.962785533915664 \tabularnewline
191 & 37 & 34.8842673399228 & 2.11573266007724 \tabularnewline
192 & 32 & 32.7885187728117 & -0.788518772811717 \tabularnewline
193 & 38 & 34.9882593957567 & 3.01174060424333 \tabularnewline
194 & 31 & 34.1647729935997 & -3.16477299359974 \tabularnewline
195 & 37 & 33.9536442386842 & 3.04635576131575 \tabularnewline
196 & 33 & 32.8504053507431 & 0.149594649256926 \tabularnewline
197 & 30 & 32.025353118356 & -2.02535311835603 \tabularnewline
198 & 30 & 28.5719286581844 & 1.42807134181559 \tabularnewline
199 & 31 & 32.5262311007677 & -1.52623110076767 \tabularnewline
200 & 32 & 33.068188554462 & -1.06818855446198 \tabularnewline
201 & 34 & 33.4210205780107 & 0.578979421989288 \tabularnewline
202 & 36 & 34.1311811313129 & 1.86881886868705 \tabularnewline
203 & 37 & 34.7917615805042 & 2.20823841949581 \tabularnewline
204 & 36 & 34.1127296169237 & 1.88727038307630 \tabularnewline
205 & 33 & 33.6540333879413 & -0.654033387941283 \tabularnewline
206 & 33 & 33.3166404880764 & -0.316640488076399 \tabularnewline
207 & 33 & 33.8920629907193 & -0.892062990719312 \tabularnewline
208 & 44 & 36.2001953738055 & 7.79980462619453 \tabularnewline
209 & 39 & 32.6326994119541 & 6.36730058804593 \tabularnewline
210 & 32 & 31.4927294576825 & 0.507270542317505 \tabularnewline
211 & 35 & 34.9674393063205 & 0.0325606936794515 \tabularnewline
212 & 25 & 30.4145072746199 & -5.41450727461987 \tabularnewline
213 & 35 & 33.9470670548107 & 1.05293294518926 \tabularnewline
214 & 34 & 36.2129671466562 & -2.21296714665616 \tabularnewline
215 & 35 & 33.980066804729 & 1.01993319527097 \tabularnewline
216 & 39 & 35.1356424059285 & 3.86435759407153 \tabularnewline
217 & 33 & 33.7596042567927 & -0.75960425679275 \tabularnewline
218 & 36 & 34.990118562569 & 1.00988143743099 \tabularnewline
219 & 32 & 33.9078847092995 & -1.90788470929949 \tabularnewline
220 & 32 & 31.375068186663 & 0.624931813337028 \tabularnewline
221 & 36 & 31.5794929443668 & 4.42050705563324 \tabularnewline
222 & 32 & 31.6731002243884 & 0.326899775611623 \tabularnewline
223 & 34 & 32.727064338185 & 1.27293566181502 \tabularnewline
224 & 33 & 32.8037483790234 & 0.196251620976623 \tabularnewline
225 & 35 & 32.8803431615477 & 2.11965683845234 \tabularnewline
226 & 30 & 33.4079554685778 & -3.40795546857781 \tabularnewline
227 & 38 & 32.2263398962299 & 5.77366010377008 \tabularnewline
228 & 34 & 32.2625991093499 & 1.73740089065011 \tabularnewline
229 & 33 & 38.174181741376 & -5.17418174137598 \tabularnewline
230 & 32 & 33.6789728278899 & -1.67897282788993 \tabularnewline
231 & 31 & 33.7157038942203 & -2.71570389422033 \tabularnewline
232 & 30 & 32.6291216359985 & -2.62912163599854 \tabularnewline
233 & 27 & 34.1585784046226 & -7.15857840462257 \tabularnewline
234 & 31 & 32.2344066348069 & -1.23440663480688 \tabularnewline
235 & 30 & 33.757732107193 & -3.75773210719297 \tabularnewline
236 & 32 & 29.5418233632483 & 2.45817663675171 \tabularnewline
237 & 35 & 33.5998375078707 & 1.40016249212932 \tabularnewline
238 & 28 & 29.2484071014825 & -1.2484071014825 \tabularnewline
239 & 33 & 33.2297372052665 & -0.229737205266491 \tabularnewline
240 & 35 & 30.4939479246055 & 4.50605207539446 \tabularnewline
241 & 35 & 32.2355844309366 & 2.76441556906341 \tabularnewline
242 & 32 & 34.0714590501603 & -2.07145905016035 \tabularnewline
243 & 21 & 26.6188700603556 & -5.61887006035564 \tabularnewline
244 & 20 & 27.5616608286921 & -7.56166082869212 \tabularnewline
245 & 34 & 31.0396237119245 & 2.96037628807546 \tabularnewline
246 & 32 & 31.8534829844785 & 0.146517015521537 \tabularnewline
247 & 34 & 34.1909794879922 & -0.190979487992215 \tabularnewline
248 & 32 & 33.7349635926304 & -1.7349635926304 \tabularnewline
249 & 33 & 34.3146138371325 & -1.31461383713253 \tabularnewline
250 & 33 & 33.3540529250894 & -0.354052925089426 \tabularnewline
251 & 37 & 34.3285763889004 & 2.67142361109964 \tabularnewline
252 & 32 & 32.5156422466873 & -0.515642246687265 \tabularnewline
253 & 34 & 35.1749140097538 & -1.17491400975384 \tabularnewline
254 & 30 & 32.2205203585657 & -2.22052035856572 \tabularnewline
255 & 30 & 30.9375038056904 & -0.937503805690408 \tabularnewline
256 & 38 & 32.8374175062401 & 5.16258249375992 \tabularnewline
257 & 36 & 35.4321076240205 & 0.567892375979483 \tabularnewline
258 & 32 & 30.8228152154705 & 1.17718478452953 \tabularnewline
259 & 34 & 35.5722450624236 & -1.57224506242363 \tabularnewline
260 & 33 & 33.8667409558743 & -0.86674095587434 \tabularnewline
261 & 27 & 27.1657366265918 & -0.165736626591792 \tabularnewline
262 & 32 & 33.4876894551457 & -1.48768945514570 \tabularnewline
263 & 34 & 35.9522582876297 & -1.95225828762967 \tabularnewline
264 & 29 & 30.8779977961901 & -1.87799779619012 \tabularnewline
265 & 35 & 33.3129091716643 & 1.68709082833572 \tabularnewline
266 & 27 & 31.7625560380775 & -4.76255603807745 \tabularnewline
267 & 33 & 35.2309047744943 & -2.23090477449431 \tabularnewline
268 & 38 & 32.9971069902323 & 5.00289300976775 \tabularnewline
269 & 36 & 34.9057688000415 & 1.09423119995850 \tabularnewline
270 & 33 & 33.9417699081685 & -0.941769908168503 \tabularnewline
271 & 39 & 31.8543804268134 & 7.1456195731866 \tabularnewline
272 & 29 & 31.9018723096723 & -2.9018723096723 \tabularnewline
273 & 32 & 33.2007741017267 & -1.20077410172675 \tabularnewline
274 & 34 & 28.234485220508 & 5.765514779492 \tabularnewline
275 & 38 & 33.9557194771489 & 4.0442805228511 \tabularnewline
276 & 17 & 25.0831294444403 & -8.08312944444032 \tabularnewline
277 & 35 & 34.599580765425 & 0.400419234574966 \tabularnewline
278 & 32 & 33.9221276148621 & -1.9221276148621 \tabularnewline
279 & 34 & 33.584607901659 & 0.415392098340985 \tabularnewline
280 & 36 & 34.0931765819314 & 1.90682341806859 \tabularnewline
281 & 31 & 35.5254988323898 & -4.52549883238982 \tabularnewline
282 & 35 & 34.0788444180547 & 0.92115558194532 \tabularnewline
283 & 29 & 29.5941600765066 & -0.594160076506555 \tabularnewline
284 & 22 & 23.9943184072973 & -1.99431840729729 \tabularnewline
285 & 41 & 36.2496089546724 & 4.75039104532755 \tabularnewline
286 & 36 & 33.3092551201821 & 2.69074487981793 \tabularnewline
287 & 42 & 38.1676938158166 & 3.83230618418341 \tabularnewline
288 & 33 & 32.2335091924719 & 0.766490807528059 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113583&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]38[/C][C]37.0828836506427[/C][C]0.917116349357299[/C][/ROW]
[ROW][C]2[/C][C]32[/C][C]36.4623829892977[/C][C]-4.46238298929768[/C][/ROW]
[ROW][C]3[/C][C]35[/C][C]33.3724173657143[/C][C]1.62758263428573[/C][/ROW]
[ROW][C]4[/C][C]33[/C][C]31.6767434776329[/C][C]1.32325652236714[/C][/ROW]
[ROW][C]5[/C][C]37[/C][C]34.0489730739423[/C][C]2.95102692605774[/C][/ROW]
[ROW][C]6[/C][C]29[/C][C]34.0293307806359[/C][C]-5.02933078063587[/C][/ROW]
[ROW][C]7[/C][C]31[/C][C]37.1761975940821[/C][C]-6.17619759408213[/C][/ROW]
[ROW][C]8[/C][C]36[/C][C]34.3629160885620[/C][C]1.63708391143804[/C][/ROW]
[ROW][C]9[/C][C]35[/C][C]34.9179256689017[/C][C]0.082074331098265[/C][/ROW]
[ROW][C]10[/C][C]38[/C][C]35.2981549657601[/C][C]2.70184503423991[/C][/ROW]
[ROW][C]11[/C][C]31[/C][C]35.2488681982313[/C][C]-4.24886819823132[/C][/ROW]
[ROW][C]12[/C][C]34[/C][C]35.1327857402294[/C][C]-1.13278574022935[/C][/ROW]
[ROW][C]13[/C][C]35[/C][C]35.6310589030036[/C][C]-0.631058903003556[/C][/ROW]
[ROW][C]14[/C][C]38[/C][C]36.5240534955767[/C][C]1.47594650442327[/C][/ROW]
[ROW][C]15[/C][C]37[/C][C]34.2003034721785[/C][C]2.7996965278215[/C][/ROW]
[ROW][C]16[/C][C]33[/C][C]32.5747494238494[/C][C]0.425250576150586[/C][/ROW]
[ROW][C]17[/C][C]32[/C][C]34.2509841074893[/C][C]-2.2509841074893[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]36.7921477224975[/C][C]1.20785227750245[/C][/ROW]
[ROW][C]19[/C][C]38[/C][C]36.2233916620422[/C][C]1.77660833795775[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.3827128832125[/C][C]-1.38271288321246[/C][/ROW]
[ROW][C]21[/C][C]33[/C][C]32.5373369868364[/C][C]0.462663013163614[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]33.0762444948012[/C][C]-2.07624449480121[/C][/ROW]
[ROW][C]23[/C][C]38[/C][C]37.2593695604799[/C][C]0.740630439520082[/C][/ROW]
[ROW][C]24[/C][C]39[/C][C]35.7261051999171[/C][C]3.27389480008291[/C][/ROW]
[ROW][C]25[/C][C]32[/C][C]36.0449573270786[/C][C]-4.04495732707861[/C][/ROW]
[ROW][C]26[/C][C]32[/C][C]37.9966340505096[/C][C]-5.99663405050956[/C][/ROW]
[ROW][C]27[/C][C]35[/C][C]34.3584141431531[/C][C]0.641585856846894[/C][/ROW]
[ROW][C]28[/C][C]37[/C][C]33.9022714344531[/C][C]3.09772856554691[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]33.8741927904608[/C][C]-0.874192790460846[/C][/ROW]
[ROW][C]30[/C][C]33[/C][C]33.2531000167473[/C][C]-0.253100016747282[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]32.7529676871607[/C][C]-1.75296768716074[/C][/ROW]
[ROW][C]32[/C][C]32[/C][C]29.4623719150249[/C][C]2.53762808497511[/C][/ROW]
[ROW][C]33[/C][C]31[/C][C]35.150555883936[/C][C]-4.15055588393598[/C][/ROW]
[ROW][C]34[/C][C]37[/C][C]34.3348374445697[/C][C]2.66516255543029[/C][/ROW]
[ROW][C]35[/C][C]30[/C][C]33.3269381901243[/C][C]-3.32693819012429[/C][/ROW]
[ROW][C]36[/C][C]33[/C][C]31.2517163758672[/C][C]1.74828362413285[/C][/ROW]
[ROW][C]37[/C][C]31[/C][C]30.2519731183128[/C][C]0.748026881687208[/C][/ROW]
[ROW][C]38[/C][C]33[/C][C]34.2173922452025[/C][C]-1.2173922452025[/C][/ROW]
[ROW][C]39[/C][C]31[/C][C]31.8035997349508[/C][C]-0.803599734950756[/C][/ROW]
[ROW][C]40[/C][C]33[/C][C]33.9902752484628[/C][C]-0.99027524846281[/C][/ROW]
[ROW][C]41[/C][C]32[/C][C]34.8498940504015[/C][C]-2.84989405040150[/C][/ROW]
[ROW][C]42[/C][C]33[/C][C]33.9658011075445[/C][C]-0.96580110754448[/C][/ROW]
[ROW][C]43[/C][C]32[/C][C]36.3719654511312[/C][C]-4.3719654511312[/C][/ROW]
[ROW][C]44[/C][C]33[/C][C]33.6829094177166[/C][C]-0.682909417716625[/C][/ROW]
[ROW][C]45[/C][C]28[/C][C]35.6728710443239[/C][C]-7.67287104432389[/C][/ROW]
[ROW][C]46[/C][C]35[/C][C]34.9946097097401[/C][C]0.00539029025986888[/C][/ROW]
[ROW][C]47[/C][C]39[/C][C]35.9223869435173[/C][C]3.07761305648274[/C][/ROW]
[ROW][C]48[/C][C]34[/C][C]33.6219202821202[/C][C]0.378079717879798[/C][/ROW]
[ROW][C]49[/C][C]38[/C][C]35.1112842801106[/C][C]2.88871571988939[/C][/ROW]
[ROW][C]50[/C][C]32[/C][C]35.2003520596993[/C][C]-3.20035205969928[/C][/ROW]
[ROW][C]51[/C][C]38[/C][C]33.549056816008[/C][C]4.45094318399196[/C][/ROW]
[ROW][C]52[/C][C]30[/C][C]32.239304949111[/C][C]-2.23930494911098[/C][/ROW]
[ROW][C]53[/C][C]33[/C][C]32.1599535574394[/C][C]0.84004644256058[/C][/ROW]
[ROW][C]54[/C][C]38[/C][C]34.5105151703861[/C][C]3.48948482961393[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]31.0396129136868[/C][C]0.960387086313191[/C][/ROW]
[ROW][C]56[/C][C]35[/C][C]34.8795385246239[/C][C]0.120461475376136[/C][/ROW]
[ROW][C]57[/C][C]34[/C][C]36.6072254619745[/C][C]-2.60722546197452[/C][/ROW]
[ROW][C]58[/C][C]34[/C][C]32.0316141740254[/C][C]1.96838582597462[/C][/ROW]
[ROW][C]59[/C][C]36[/C][C]34.856471234275[/C][C]1.143528765725[/C][/ROW]
[ROW][C]60[/C][C]34[/C][C]34.7216439253016[/C][C]-0.721643925301568[/C][/ROW]
[ROW][C]61[/C][C]28[/C][C]30.9153101766513[/C][C]-2.91531017665131[/C][/ROW]
[ROW][C]62[/C][C]34[/C][C]35.538553143585[/C][C]-1.53855314358499[/C][/ROW]
[ROW][C]63[/C][C]35[/C][C]34.6245223899234[/C][C]0.375477610076617[/C][/ROW]
[ROW][C]64[/C][C]35[/C][C]32.5623656850991[/C][C]2.43763431490086[/C][/ROW]
[ROW][C]65[/C][C]31[/C][C]34.3348374445697[/C][C]-3.33483744456971[/C][/ROW]
[ROW][C]66[/C][C]37[/C][C]34.5013974490176[/C][C]2.4986025509824[/C][/ROW]
[ROW][C]67[/C][C]35[/C][C]35.8840127820268[/C][C]-0.884012782026823[/C][/ROW]
[ROW][C]68[/C][C]27[/C][C]32.1392602813415[/C][C]-5.1392602813415[/C][/ROW]
[ROW][C]69[/C][C]40[/C][C]35.9616585473426[/C][C]4.03834145265737[/C][/ROW]
[ROW][C]70[/C][C]37[/C][C]34.0949486749793[/C][C]2.90505132502066[/C][/ROW]
[ROW][C]71[/C][C]36[/C][C]34.1604267731972[/C][C]1.83957322680282[/C][/ROW]
[ROW][C]72[/C][C]38[/C][C]32.5006951788201[/C][C]5.49930482117991[/C][/ROW]
[ROW][C]73[/C][C]39[/C][C]34.839382461251[/C][C]4.160617538749[/C][/ROW]
[ROW][C]74[/C][C]41[/C][C]35.9814276539872[/C][C]5.01857234601277[/C][/ROW]
[ROW][C]75[/C][C]27[/C][C]33.6959745271495[/C][C]-6.69597452714952[/C][/ROW]
[ROW][C]76[/C][C]30[/C][C]36.6501511172821[/C][C]-6.6501511172821[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.7382728670151[/C][C]1.26172713298495[/C][/ROW]
[ROW][C]78[/C][C]31[/C][C]34.313335984451[/C][C]-3.31333598445097[/C][/ROW]
[ROW][C]79[/C][C]31[/C][C]30.3631344703887[/C][C]0.636865529611282[/C][/ROW]
[ROW][C]80[/C][C]27[/C][C]35.0779084894761[/C][C]-8.07790848947612[/C][/ROW]
[ROW][C]81[/C][C]36[/C][C]33.1736593667616[/C][C]2.82634063323839[/C][/ROW]
[ROW][C]82[/C][C]37[/C][C]34.7954820986786[/C][C]2.20451790132142[/C][/ROW]
[ROW][C]83[/C][C]33[/C][C]34.8163021881147[/C][C]-1.81630218811470[/C][/ROW]
[ROW][C]84[/C][C]34[/C][C]33.1612756280113[/C][C]0.838724371988664[/C][/ROW]
[ROW][C]85[/C][C]31[/C][C]33.7386841108048[/C][C]-2.73868411080479[/C][/ROW]
[ROW][C]86[/C][C]39[/C][C]34.8891656542269[/C][C]4.11083434577313[/C][/ROW]
[ROW][C]87[/C][C]34[/C][C]33.9050280436004[/C][C]0.0949719563996314[/C][/ROW]
[ROW][C]88[/C][C]32[/C][C]32.0932846803044[/C][C]-0.0932846803044281[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.9517742736342[/C][C]-0.951774273634176[/C][/ROW]
[ROW][C]90[/C][C]36[/C][C]31.9653149089993[/C][C]4.03468509100072[/C][/ROW]
[ROW][C]91[/C][C]32[/C][C]35.7364137002027[/C][C]-3.73641370020271[/C][/ROW]
[ROW][C]92[/C][C]41[/C][C]34.7954820986786[/C][C]6.20451790132142[/C][/ROW]
[ROW][C]93[/C][C]28[/C][C]33.2752828475487[/C][C]-5.27528284754865[/C][/ROW]
[ROW][C]94[/C][C]30[/C][C]31.5859830544759[/C][C]-1.58598305447586[/C][/ROW]
[ROW][C]95[/C][C]36[/C][C]36.4408815291789[/C][C]-0.440881529178940[/C][/ROW]
[ROW][C]96[/C][C]35[/C][C]35.8924491327127[/C][C]-0.892449132712668[/C][/ROW]
[ROW][C]97[/C][C]31[/C][C]34.5768014526247[/C][C]-3.57680145262473[/C][/ROW]
[ROW][C]98[/C][C]34[/C][C]34.954567476918[/C][C]-0.954567476918028[/C][/ROW]
[ROW][C]99[/C][C]36[/C][C]32.2084696959715[/C][C]3.79153030402854[/C][/ROW]
[ROW][C]100[/C][C]36[/C][C]36.2820894875217[/C][C]-0.282089487521708[/C][/ROW]
[ROW][C]101[/C][C]35[/C][C]35.0255717762179[/C][C]-0.0255717762178542[/C][/ROW]
[ROW][C]102[/C][C]37[/C][C]36.1512095666127[/C][C]0.848790433387295[/C][/ROW]
[ROW][C]103[/C][C]28[/C][C]32.5840832168702[/C][C]-4.58408321687020[/C][/ROW]
[ROW][C]104[/C][C]39[/C][C]33.7910208240631[/C][C]5.20897917593694[/C][/ROW]
[ROW][C]105[/C][C]32[/C][C]36.0758818385322[/C][C]-4.07588183853225[/C][/ROW]
[ROW][C]106[/C][C]35[/C][C]36.3156813498085[/C][C]-1.31568134980851[/C][/ROW]
[ROW][C]107[/C][C]39[/C][C]36.8588165996325[/C][C]2.14118340036746[/C][/ROW]
[ROW][C]108[/C][C]35[/C][C]34.626597628388[/C][C]0.373402371611966[/C][/ROW]
[ROW][C]109[/C][C]42[/C][C]37.5425535974868[/C][C]4.45744640251324[/C][/ROW]
[ROW][C]110[/C][C]34[/C][C]32.4922588281342[/C][C]1.50774117186575[/C][/ROW]
[ROW][C]111[/C][C]33[/C][C]33.2425884275968[/C][C]-0.242588427596785[/C][/ROW]
[ROW][C]112[/C][C]41[/C][C]33.5611472181761[/C][C]7.43885278182391[/C][/ROW]
[ROW][C]113[/C][C]34[/C][C]34.7815195469107[/C][C]-0.781519546910745[/C][/ROW]
[ROW][C]114[/C][C]32[/C][C]35.4067757803411[/C][C]-3.40677578034105[/C][/ROW]
[ROW][C]115[/C][C]40[/C][C]33.6499989261125[/C][C]6.35000107388755[/C][/ROW]
[ROW][C]116[/C][C]40[/C][C]33.6947837482324[/C][C]6.30521625176763[/C][/ROW]
[ROW][C]117[/C][C]35[/C][C]33.314554451374[/C][C]1.68544554862598[/C][/ROW]
[ROW][C]118[/C][C]36[/C][C]36.2082513141447[/C][C]-0.208251314144699[/C][/ROW]
[ROW][C]119[/C][C]37[/C][C]32.6756915339538[/C][C]4.32430846604617[/C][/ROW]
[ROW][C]120[/C][C]27[/C][C]33.0669107017804[/C][C]-6.06691070178043[/C][/ROW]
[ROW][C]121[/C][C]39[/C][C]35.6701144351766[/C][C]3.32988556482339[/C][/ROW]
[ROW][C]122[/C][C]38[/C][C]35.8831153396919[/C][C]2.11688466030811[/C][/ROW]
[ROW][C]123[/C][C]31[/C][C]35.1701981772424[/C][C]-4.17019817724238[/C][/ROW]
[ROW][C]124[/C][C]33[/C][C]33.2640898877155[/C][C]-0.264089887715528[/C][/ROW]
[ROW][C]125[/C][C]32[/C][C]35.5404123103973[/C][C]-3.54041231039733[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]38.9655420549244[/C][C]0.0344579450756088[/C][/ROW]
[ROW][C]127[/C][C]36[/C][C]33.3322353367665[/C][C]2.66776466323347[/C][/ROW]
[ROW][C]128[/C][C]33[/C][C]34.0359079645094[/C][C]-1.03590796450937[/C][/ROW]
[ROW][C]129[/C][C]33[/C][C]32.6083412861362[/C][C]0.391658713863788[/C][/ROW]
[ROW][C]130[/C][C]32[/C][C]29.9576723969995[/C][C]2.04232760300050[/C][/ROW]
[ROW][C]131[/C][C]37[/C][C]36.7660175036318[/C][C]0.23398249636825[/C][/ROW]
[ROW][C]132[/C][C]30[/C][C]29.6502173079392[/C][C]0.349782692060791[/C][/ROW]
[ROW][C]133[/C][C]38[/C][C]34.6780368993114[/C][C]3.32196310068863[/C][/ROW]
[ROW][C]134[/C][C]29[/C][C]33.2136123412696[/C][C]-4.2136123412696[/C][/ROW]
[ROW][C]135[/C][C]22[/C][C]30.2369595837534[/C][C]-8.23695958375344[/C][/ROW]
[ROW][C]136[/C][C]35[/C][C]33.4128667656694[/C][C]1.58713323433064[/C][/ROW]
[ROW][C]137[/C][C]35[/C][C]31.6037531981825[/C][C]3.39624680181751[/C][/ROW]
[ROW][C]138[/C][C]34[/C][C]33.786392065316[/C][C]0.213607934683997[/C][/ROW]
[ROW][C]139[/C][C]35[/C][C]31.2190219559153[/C][C]3.78097804408471[/C][/ROW]
[ROW][C]140[/C][C]34[/C][C]33.0808602707608[/C][C]0.919139729239178[/C][/ROW]
[ROW][C]141[/C][C]37[/C][C]31.3422737101593[/C][C]5.65772628984073[/C][/ROW]
[ROW][C]142[/C][C]35[/C][C]32.94171052241[/C][C]2.05828947759001[/C][/ROW]
[ROW][C]143[/C][C]23[/C][C]32.1691980921461[/C][C]-9.16919809214609[/C][/ROW]
[ROW][C]144[/C][C]31[/C][C]35.7205789988351[/C][C]-4.7205789988351[/C][/ROW]
[ROW][C]145[/C][C]27[/C][C]33.8040859334960[/C][C]-6.80408593349595[/C][/ROW]
[ROW][C]146[/C][C]36[/C][C]34.1716327158177[/C][C]1.82836728418226[/C][/ROW]
[ROW][C]147[/C][C]31[/C][C]32.8055204720713[/C][C]-1.80552047207131[/C][/ROW]
[ROW][C]148[/C][C]32[/C][C]33.5231426687945[/C][C]-1.52314266879455[/C][/ROW]
[ROW][C]149[/C][C]39[/C][C]34.7161177242196[/C][C]4.28388227578042[/C][/ROW]
[ROW][C]150[/C][C]37[/C][C]37.9957366081746[/C][C]-0.995736608174622[/C][/ROW]
[ROW][C]151[/C][C]38[/C][C]33.3539528685376[/C][C]4.64604713146241[/C][/ROW]
[ROW][C]152[/C][C]39[/C][C]34.3889560597104[/C][C]4.61104394028959[/C][/ROW]
[ROW][C]153[/C][C]34[/C][C]35.6915386303655[/C][C]-1.69153863036545[/C][/ROW]
[ROW][C]154[/C][C]31[/C][C]32.5885721794916[/C][C]-1.58857217949161[/C][/ROW]
[ROW][C]155[/C][C]37[/C][C]32.4380499652762[/C][C]4.56195003472379[/C][/ROW]
[ROW][C]156[/C][C]36[/C][C]33.3322353367665[/C][C]2.66776466323347[/C][/ROW]
[ROW][C]157[/C][C]32[/C][C]34.313335984451[/C][C]-2.31333598445097[/C][/ROW]
[ROW][C]158[/C][C]38[/C][C]32.496963862408[/C][C]5.50303613759202[/C][/ROW]
[ROW][C]159[/C][C]26[/C][C]29.9389383442658[/C][C]-3.93893834426577[/C][/ROW]
[ROW][C]160[/C][C]26[/C][C]31.3227314734047[/C][C]-5.32273147340471[/C][/ROW]
[ROW][C]161[/C][C]33[/C][C]35.8301080539887[/C][C]-2.83010805398873[/C][/ROW]
[ROW][C]162[/C][C]39[/C][C]34.2021854306128[/C][C]4.79781456938723[/C][/ROW]
[ROW][C]163[/C][C]30[/C][C]27.8525235701755[/C][C]2.14747642982449[/C][/ROW]
[ROW][C]164[/C][C]33[/C][C]31.4498038023749[/C][C]1.55019619762508[/C][/ROW]
[ROW][C]165[/C][C]25[/C][C]29.9452994564870[/C][C]-4.94529945648696[/C][/ROW]
[ROW][C]166[/C][C]38[/C][C]34.0611635326622[/C][C]3.93883646733783[/C][/ROW]
[ROW][C]167[/C][C]37[/C][C]30.6434191560294[/C][C]6.35658084397057[/C][/ROW]
[ROW][C]168[/C][C]31[/C][C]33.9295892582831[/C][C]-2.9295892582831[/C][/ROW]
[ROW][C]169[/C][C]37[/C][C]35.2739076947318[/C][C]1.7260923052682[/C][/ROW]
[ROW][C]170[/C][C]35[/C][C]36.2496982129866[/C][C]-1.24969821298656[/C][/ROW]
[ROW][C]171[/C][C]25[/C][C]30.5423372497994[/C][C]-5.54233724979938[/C][/ROW]
[ROW][C]172[/C][C]28[/C][C]34.5975055269604[/C][C]-6.59750552696038[/C][/ROW]
[ROW][C]173[/C][C]35[/C][C]32.571028905675[/C][C]2.42897109432497[/C][/ROW]
[ROW][C]174[/C][C]33[/C][C]34.9413090874548[/C][C]-1.94130908745475[/C][/ROW]
[ROW][C]175[/C][C]30[/C][C]31.0069292919727[/C][C]-1.00692929197268[/C][/ROW]
[ROW][C]176[/C][C]31[/C][C]32.4661394075062[/C][C]-1.46613940750618[/C][/ROW]
[ROW][C]177[/C][C]37[/C][C]35.4234552016824[/C][C]1.57654479831764[/C][/ROW]
[ROW][C]178[/C][C]36[/C][C]35.3355782010108[/C][C]0.664421798989156[/C][/ROW]
[ROW][C]179[/C][C]30[/C][C]32.8607008682413[/C][C]-2.86070086824126[/C][/ROW]
[ROW][C]180[/C][C]36[/C][C]33.0578037786497[/C][C]2.94219622135031[/C][/ROW]
[ROW][C]181[/C][C]32[/C][C]35.3872335435865[/C][C]-3.38723354358649[/C][/ROW]
[ROW][C]182[/C][C]28[/C][C]27.4720782016648[/C][C]0.527921798335158[/C][/ROW]
[ROW][C]183[/C][C]36[/C][C]33.5238348377149[/C][C]2.47616516228510[/C][/ROW]
[ROW][C]184[/C][C]34[/C][C]34.7209733528567[/C][C]-0.720973352856674[/C][/ROW]
[ROW][C]185[/C][C]31[/C][C]35.5944149104376[/C][C]-4.59441491043756[/C][/ROW]
[ROW][C]186[/C][C]28[/C][C]29.719360255877[/C][C]-1.71936025587699[/C][/ROW]
[ROW][C]187[/C][C]36[/C][C]31.4572654457959[/C][C]4.54273455420408[/C][/ROW]
[ROW][C]188[/C][C]36[/C][C]33.2473042601082[/C][C]2.75269573989176[/C][/ROW]
[ROW][C]189[/C][C]40[/C][C]36.2568675092286[/C][C]3.74313249077142[/C][/ROW]
[ROW][C]190[/C][C]33[/C][C]32.0372144660843[/C][C]0.962785533915664[/C][/ROW]
[ROW][C]191[/C][C]37[/C][C]34.8842673399228[/C][C]2.11573266007724[/C][/ROW]
[ROW][C]192[/C][C]32[/C][C]32.7885187728117[/C][C]-0.788518772811717[/C][/ROW]
[ROW][C]193[/C][C]38[/C][C]34.9882593957567[/C][C]3.01174060424333[/C][/ROW]
[ROW][C]194[/C][C]31[/C][C]34.1647729935997[/C][C]-3.16477299359974[/C][/ROW]
[ROW][C]195[/C][C]37[/C][C]33.9536442386842[/C][C]3.04635576131575[/C][/ROW]
[ROW][C]196[/C][C]33[/C][C]32.8504053507431[/C][C]0.149594649256926[/C][/ROW]
[ROW][C]197[/C][C]30[/C][C]32.025353118356[/C][C]-2.02535311835603[/C][/ROW]
[ROW][C]198[/C][C]30[/C][C]28.5719286581844[/C][C]1.42807134181559[/C][/ROW]
[ROW][C]199[/C][C]31[/C][C]32.5262311007677[/C][C]-1.52623110076767[/C][/ROW]
[ROW][C]200[/C][C]32[/C][C]33.068188554462[/C][C]-1.06818855446198[/C][/ROW]
[ROW][C]201[/C][C]34[/C][C]33.4210205780107[/C][C]0.578979421989288[/C][/ROW]
[ROW][C]202[/C][C]36[/C][C]34.1311811313129[/C][C]1.86881886868705[/C][/ROW]
[ROW][C]203[/C][C]37[/C][C]34.7917615805042[/C][C]2.20823841949581[/C][/ROW]
[ROW][C]204[/C][C]36[/C][C]34.1127296169237[/C][C]1.88727038307630[/C][/ROW]
[ROW][C]205[/C][C]33[/C][C]33.6540333879413[/C][C]-0.654033387941283[/C][/ROW]
[ROW][C]206[/C][C]33[/C][C]33.3166404880764[/C][C]-0.316640488076399[/C][/ROW]
[ROW][C]207[/C][C]33[/C][C]33.8920629907193[/C][C]-0.892062990719312[/C][/ROW]
[ROW][C]208[/C][C]44[/C][C]36.2001953738055[/C][C]7.79980462619453[/C][/ROW]
[ROW][C]209[/C][C]39[/C][C]32.6326994119541[/C][C]6.36730058804593[/C][/ROW]
[ROW][C]210[/C][C]32[/C][C]31.4927294576825[/C][C]0.507270542317505[/C][/ROW]
[ROW][C]211[/C][C]35[/C][C]34.9674393063205[/C][C]0.0325606936794515[/C][/ROW]
[ROW][C]212[/C][C]25[/C][C]30.4145072746199[/C][C]-5.41450727461987[/C][/ROW]
[ROW][C]213[/C][C]35[/C][C]33.9470670548107[/C][C]1.05293294518926[/C][/ROW]
[ROW][C]214[/C][C]34[/C][C]36.2129671466562[/C][C]-2.21296714665616[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]33.980066804729[/C][C]1.01993319527097[/C][/ROW]
[ROW][C]216[/C][C]39[/C][C]35.1356424059285[/C][C]3.86435759407153[/C][/ROW]
[ROW][C]217[/C][C]33[/C][C]33.7596042567927[/C][C]-0.75960425679275[/C][/ROW]
[ROW][C]218[/C][C]36[/C][C]34.990118562569[/C][C]1.00988143743099[/C][/ROW]
[ROW][C]219[/C][C]32[/C][C]33.9078847092995[/C][C]-1.90788470929949[/C][/ROW]
[ROW][C]220[/C][C]32[/C][C]31.375068186663[/C][C]0.624931813337028[/C][/ROW]
[ROW][C]221[/C][C]36[/C][C]31.5794929443668[/C][C]4.42050705563324[/C][/ROW]
[ROW][C]222[/C][C]32[/C][C]31.6731002243884[/C][C]0.326899775611623[/C][/ROW]
[ROW][C]223[/C][C]34[/C][C]32.727064338185[/C][C]1.27293566181502[/C][/ROW]
[ROW][C]224[/C][C]33[/C][C]32.8037483790234[/C][C]0.196251620976623[/C][/ROW]
[ROW][C]225[/C][C]35[/C][C]32.8803431615477[/C][C]2.11965683845234[/C][/ROW]
[ROW][C]226[/C][C]30[/C][C]33.4079554685778[/C][C]-3.40795546857781[/C][/ROW]
[ROW][C]227[/C][C]38[/C][C]32.2263398962299[/C][C]5.77366010377008[/C][/ROW]
[ROW][C]228[/C][C]34[/C][C]32.2625991093499[/C][C]1.73740089065011[/C][/ROW]
[ROW][C]229[/C][C]33[/C][C]38.174181741376[/C][C]-5.17418174137598[/C][/ROW]
[ROW][C]230[/C][C]32[/C][C]33.6789728278899[/C][C]-1.67897282788993[/C][/ROW]
[ROW][C]231[/C][C]31[/C][C]33.7157038942203[/C][C]-2.71570389422033[/C][/ROW]
[ROW][C]232[/C][C]30[/C][C]32.6291216359985[/C][C]-2.62912163599854[/C][/ROW]
[ROW][C]233[/C][C]27[/C][C]34.1585784046226[/C][C]-7.15857840462257[/C][/ROW]
[ROW][C]234[/C][C]31[/C][C]32.2344066348069[/C][C]-1.23440663480688[/C][/ROW]
[ROW][C]235[/C][C]30[/C][C]33.757732107193[/C][C]-3.75773210719297[/C][/ROW]
[ROW][C]236[/C][C]32[/C][C]29.5418233632483[/C][C]2.45817663675171[/C][/ROW]
[ROW][C]237[/C][C]35[/C][C]33.5998375078707[/C][C]1.40016249212932[/C][/ROW]
[ROW][C]238[/C][C]28[/C][C]29.2484071014825[/C][C]-1.2484071014825[/C][/ROW]
[ROW][C]239[/C][C]33[/C][C]33.2297372052665[/C][C]-0.229737205266491[/C][/ROW]
[ROW][C]240[/C][C]35[/C][C]30.4939479246055[/C][C]4.50605207539446[/C][/ROW]
[ROW][C]241[/C][C]35[/C][C]32.2355844309366[/C][C]2.76441556906341[/C][/ROW]
[ROW][C]242[/C][C]32[/C][C]34.0714590501603[/C][C]-2.07145905016035[/C][/ROW]
[ROW][C]243[/C][C]21[/C][C]26.6188700603556[/C][C]-5.61887006035564[/C][/ROW]
[ROW][C]244[/C][C]20[/C][C]27.5616608286921[/C][C]-7.56166082869212[/C][/ROW]
[ROW][C]245[/C][C]34[/C][C]31.0396237119245[/C][C]2.96037628807546[/C][/ROW]
[ROW][C]246[/C][C]32[/C][C]31.8534829844785[/C][C]0.146517015521537[/C][/ROW]
[ROW][C]247[/C][C]34[/C][C]34.1909794879922[/C][C]-0.190979487992215[/C][/ROW]
[ROW][C]248[/C][C]32[/C][C]33.7349635926304[/C][C]-1.7349635926304[/C][/ROW]
[ROW][C]249[/C][C]33[/C][C]34.3146138371325[/C][C]-1.31461383713253[/C][/ROW]
[ROW][C]250[/C][C]33[/C][C]33.3540529250894[/C][C]-0.354052925089426[/C][/ROW]
[ROW][C]251[/C][C]37[/C][C]34.3285763889004[/C][C]2.67142361109964[/C][/ROW]
[ROW][C]252[/C][C]32[/C][C]32.5156422466873[/C][C]-0.515642246687265[/C][/ROW]
[ROW][C]253[/C][C]34[/C][C]35.1749140097538[/C][C]-1.17491400975384[/C][/ROW]
[ROW][C]254[/C][C]30[/C][C]32.2205203585657[/C][C]-2.22052035856572[/C][/ROW]
[ROW][C]255[/C][C]30[/C][C]30.9375038056904[/C][C]-0.937503805690408[/C][/ROW]
[ROW][C]256[/C][C]38[/C][C]32.8374175062401[/C][C]5.16258249375992[/C][/ROW]
[ROW][C]257[/C][C]36[/C][C]35.4321076240205[/C][C]0.567892375979483[/C][/ROW]
[ROW][C]258[/C][C]32[/C][C]30.8228152154705[/C][C]1.17718478452953[/C][/ROW]
[ROW][C]259[/C][C]34[/C][C]35.5722450624236[/C][C]-1.57224506242363[/C][/ROW]
[ROW][C]260[/C][C]33[/C][C]33.8667409558743[/C][C]-0.86674095587434[/C][/ROW]
[ROW][C]261[/C][C]27[/C][C]27.1657366265918[/C][C]-0.165736626591792[/C][/ROW]
[ROW][C]262[/C][C]32[/C][C]33.4876894551457[/C][C]-1.48768945514570[/C][/ROW]
[ROW][C]263[/C][C]34[/C][C]35.9522582876297[/C][C]-1.95225828762967[/C][/ROW]
[ROW][C]264[/C][C]29[/C][C]30.8779977961901[/C][C]-1.87799779619012[/C][/ROW]
[ROW][C]265[/C][C]35[/C][C]33.3129091716643[/C][C]1.68709082833572[/C][/ROW]
[ROW][C]266[/C][C]27[/C][C]31.7625560380775[/C][C]-4.76255603807745[/C][/ROW]
[ROW][C]267[/C][C]33[/C][C]35.2309047744943[/C][C]-2.23090477449431[/C][/ROW]
[ROW][C]268[/C][C]38[/C][C]32.9971069902323[/C][C]5.00289300976775[/C][/ROW]
[ROW][C]269[/C][C]36[/C][C]34.9057688000415[/C][C]1.09423119995850[/C][/ROW]
[ROW][C]270[/C][C]33[/C][C]33.9417699081685[/C][C]-0.941769908168503[/C][/ROW]
[ROW][C]271[/C][C]39[/C][C]31.8543804268134[/C][C]7.1456195731866[/C][/ROW]
[ROW][C]272[/C][C]29[/C][C]31.9018723096723[/C][C]-2.9018723096723[/C][/ROW]
[ROW][C]273[/C][C]32[/C][C]33.2007741017267[/C][C]-1.20077410172675[/C][/ROW]
[ROW][C]274[/C][C]34[/C][C]28.234485220508[/C][C]5.765514779492[/C][/ROW]
[ROW][C]275[/C][C]38[/C][C]33.9557194771489[/C][C]4.0442805228511[/C][/ROW]
[ROW][C]276[/C][C]17[/C][C]25.0831294444403[/C][C]-8.08312944444032[/C][/ROW]
[ROW][C]277[/C][C]35[/C][C]34.599580765425[/C][C]0.400419234574966[/C][/ROW]
[ROW][C]278[/C][C]32[/C][C]33.9221276148621[/C][C]-1.9221276148621[/C][/ROW]
[ROW][C]279[/C][C]34[/C][C]33.584607901659[/C][C]0.415392098340985[/C][/ROW]
[ROW][C]280[/C][C]36[/C][C]34.0931765819314[/C][C]1.90682341806859[/C][/ROW]
[ROW][C]281[/C][C]31[/C][C]35.5254988323898[/C][C]-4.52549883238982[/C][/ROW]
[ROW][C]282[/C][C]35[/C][C]34.0788444180547[/C][C]0.92115558194532[/C][/ROW]
[ROW][C]283[/C][C]29[/C][C]29.5941600765066[/C][C]-0.594160076506555[/C][/ROW]
[ROW][C]284[/C][C]22[/C][C]23.9943184072973[/C][C]-1.99431840729729[/C][/ROW]
[ROW][C]285[/C][C]41[/C][C]36.2496089546724[/C][C]4.75039104532755[/C][/ROW]
[ROW][C]286[/C][C]36[/C][C]33.3092551201821[/C][C]2.69074487981793[/C][/ROW]
[ROW][C]287[/C][C]42[/C][C]38.1676938158166[/C][C]3.83230618418341[/C][/ROW]
[ROW][C]288[/C][C]33[/C][C]32.2335091924719[/C][C]0.766490807528059[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113583&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113583&T=4

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
13837.08288365064270.917116349357299
23236.4623829892977-4.46238298929768
33533.37241736571431.62758263428573
43331.67674347763291.32325652236714
53734.04897307394232.95102692605774
62934.0293307806359-5.02933078063587
73137.1761975940821-6.17619759408213
83634.36291608856201.63708391143804
93534.91792566890170.082074331098265
103835.29815496576012.70184503423991
113135.2488681982313-4.24886819823132
123435.1327857402294-1.13278574022935
133535.6310589030036-0.631058903003556
143836.52405349557671.47594650442327
153734.20030347217852.7996965278215
163332.57474942384940.425250576150586
173234.2509841074893-2.2509841074893
183836.79214772249751.20785227750245
193836.22339166204221.77660833795775
203233.3827128832125-1.38271288321246
213332.53733698683640.462663013163614
223133.0762444948012-2.07624449480121
233837.25936956047990.740630439520082
243935.72610519991713.27389480008291
253236.0449573270786-4.04495732707861
263237.9966340505096-5.99663405050956
273534.35841414315310.641585856846894
283733.90227143445313.09772856554691
293333.8741927904608-0.874192790460846
303333.2531000167473-0.253100016747282
313132.7529676871607-1.75296768716074
323229.46237191502492.53762808497511
333135.150555883936-4.15055588393598
343734.33483744456972.66516255543029
353033.3269381901243-3.32693819012429
363331.25171637586721.74828362413285
373130.25197311831280.748026881687208
383334.2173922452025-1.2173922452025
393131.8035997349508-0.803599734950756
403333.9902752484628-0.99027524846281
413234.8498940504015-2.84989405040150
423333.9658011075445-0.96580110754448
433236.3719654511312-4.3719654511312
443333.6829094177166-0.682909417716625
452835.6728710443239-7.67287104432389
463534.99460970974010.00539029025986888
473935.92238694351733.07761305648274
483433.62192028212020.378079717879798
493835.11128428011062.88871571988939
503235.2003520596993-3.20035205969928
513833.5490568160084.45094318399196
523032.239304949111-2.23930494911098
533332.15995355743940.84004644256058
543834.51051517038613.48948482961393
553231.03961291368680.960387086313191
563534.87953852462390.120461475376136
573436.6072254619745-2.60722546197452
583432.03161417402541.96838582597462
593634.8564712342751.143528765725
603434.7216439253016-0.721643925301568
612830.9153101766513-2.91531017665131
623435.538553143585-1.53855314358499
633534.62452238992340.375477610076617
643532.56236568509912.43763431490086
653134.3348374445697-3.33483744456971
663734.50139744901762.4986025509824
673535.8840127820268-0.884012782026823
682732.1392602813415-5.1392602813415
694035.96165854734264.03834145265737
703734.09494867497932.90505132502066
713634.16042677319721.83957322680282
723832.50069517882015.49930482117991
733934.8393824612514.160617538749
744135.98142765398725.01857234601277
752733.6959745271495-6.69597452714952
763036.6501511172821-6.6501511172821
773735.73827286701511.26172713298495
783134.313335984451-3.31333598445097
793130.36313447038870.636865529611282
802735.0779084894761-8.07790848947612
813633.17365936676162.82634063323839
823734.79548209867862.20451790132142
833334.8163021881147-1.81630218811470
843433.16127562801130.838724371988664
853133.7386841108048-2.73868411080479
863934.88916565422694.11083434577313
873433.90502804360040.0949719563996314
883232.0932846803044-0.0932846803044281
893333.9517742736342-0.951774273634176
903631.96531490899934.03468509100072
913235.7364137002027-3.73641370020271
924134.79548209867866.20451790132142
932833.2752828475487-5.27528284754865
943031.5859830544759-1.58598305447586
953636.4408815291789-0.440881529178940
963535.8924491327127-0.892449132712668
973134.5768014526247-3.57680145262473
983434.954567476918-0.954567476918028
993632.20846969597153.79153030402854
1003636.2820894875217-0.282089487521708
1013535.0255717762179-0.0255717762178542
1023736.15120956661270.848790433387295
1032832.5840832168702-4.58408321687020
1043933.79102082406315.20897917593694
1053236.0758818385322-4.07588183853225
1063536.3156813498085-1.31568134980851
1073936.85881659963252.14118340036746
1083534.6265976283880.373402371611966
1094237.54255359748684.45744640251324
1103432.49225882813421.50774117186575
1113333.2425884275968-0.242588427596785
1124133.56114721817617.43885278182391
1133434.7815195469107-0.781519546910745
1143235.4067757803411-3.40677578034105
1154033.64999892611256.35000107388755
1164033.69478374823246.30521625176763
1173533.3145544513741.68544554862598
1183636.2082513141447-0.208251314144699
1193732.67569153395384.32430846604617
1202733.0669107017804-6.06691070178043
1213935.67011443517663.32988556482339
1223835.88311533969192.11688466030811
1233135.1701981772424-4.17019817724238
1243333.2640898877155-0.264089887715528
1253235.5404123103973-3.54041231039733
1263938.96554205492440.0344579450756088
1273633.33223533676652.66776466323347
1283334.0359079645094-1.03590796450937
1293332.60834128613620.391658713863788
1303229.95767239699952.04232760300050
1313736.76601750363180.23398249636825
1323029.65021730793920.349782692060791
1333834.67803689931143.32196310068863
1342933.2136123412696-4.2136123412696
1352230.2369595837534-8.23695958375344
1363533.41286676566941.58713323433064
1373531.60375319818253.39624680181751
1383433.7863920653160.213607934683997
1393531.21902195591533.78097804408471
1403433.08086027076080.919139729239178
1413731.34227371015935.65772628984073
1423532.941710522412.05828947759001
1432332.1691980921461-9.16919809214609
1443135.7205789988351-4.7205789988351
1452733.8040859334960-6.80408593349595
1463634.17163271581771.82836728418226
1473132.8055204720713-1.80552047207131
1483233.5231426687945-1.52314266879455
1493934.71611772421964.28388227578042
1503737.9957366081746-0.995736608174622
1513833.35395286853764.64604713146241
1523934.38895605971044.61104394028959
1533435.6915386303655-1.69153863036545
1543132.5885721794916-1.58857217949161
1553732.43804996527624.56195003472379
1563633.33223533676652.66776466323347
1573234.313335984451-2.31333598445097
1583832.4969638624085.50303613759202
1592629.9389383442658-3.93893834426577
1602631.3227314734047-5.32273147340471
1613335.8301080539887-2.83010805398873
1623934.20218543061284.79781456938723
1633027.85252357017552.14747642982449
1643331.44980380237491.55019619762508
1652529.9452994564870-4.94529945648696
1663834.06116353266223.93883646733783
1673730.64341915602946.35658084397057
1683133.9295892582831-2.9295892582831
1693735.27390769473181.7260923052682
1703536.2496982129866-1.24969821298656
1712530.5423372497994-5.54233724979938
1722834.5975055269604-6.59750552696038
1733532.5710289056752.42897109432497
1743334.9413090874548-1.94130908745475
1753031.0069292919727-1.00692929197268
1763132.4661394075062-1.46613940750618
1773735.42345520168241.57654479831764
1783635.33557820101080.664421798989156
1793032.8607008682413-2.86070086824126
1803633.05780377864972.94219622135031
1813235.3872335435865-3.38723354358649
1822827.47207820166480.527921798335158
1833633.52383483771492.47616516228510
1843434.7209733528567-0.720973352856674
1853135.5944149104376-4.59441491043756
1862829.719360255877-1.71936025587699
1873631.45726544579594.54273455420408
1883633.24730426010822.75269573989176
1894036.25686750922863.74313249077142
1903332.03721446608430.962785533915664
1913734.88426733992282.11573266007724
1923232.7885187728117-0.788518772811717
1933834.98825939575673.01174060424333
1943134.1647729935997-3.16477299359974
1953733.95364423868423.04635576131575
1963332.85040535074310.149594649256926
1973032.025353118356-2.02535311835603
1983028.57192865818441.42807134181559
1993132.5262311007677-1.52623110076767
2003233.068188554462-1.06818855446198
2013433.42102057801070.578979421989288
2023634.13118113131291.86881886868705
2033734.79176158050422.20823841949581
2043634.11272961692371.88727038307630
2053333.6540333879413-0.654033387941283
2063333.3166404880764-0.316640488076399
2073333.8920629907193-0.892062990719312
2084436.20019537380557.79980462619453
2093932.63269941195416.36730058804593
2103231.49272945768250.507270542317505
2113534.96743930632050.0325606936794515
2122530.4145072746199-5.41450727461987
2133533.94706705481071.05293294518926
2143436.2129671466562-2.21296714665616
2153533.9800668047291.01993319527097
2163935.13564240592853.86435759407153
2173333.7596042567927-0.75960425679275
2183634.9901185625691.00988143743099
2193233.9078847092995-1.90788470929949
2203231.3750681866630.624931813337028
2213631.57949294436684.42050705563324
2223231.67310022438840.326899775611623
2233432.7270643381851.27293566181502
2243332.80374837902340.196251620976623
2253532.88034316154772.11965683845234
2263033.4079554685778-3.40795546857781
2273832.22633989622995.77366010377008
2283432.26259910934991.73740089065011
2293338.174181741376-5.17418174137598
2303233.6789728278899-1.67897282788993
2313133.7157038942203-2.71570389422033
2323032.6291216359985-2.62912163599854
2332734.1585784046226-7.15857840462257
2343132.2344066348069-1.23440663480688
2353033.757732107193-3.75773210719297
2363229.54182336324832.45817663675171
2373533.59983750787071.40016249212932
2382829.2484071014825-1.2484071014825
2393333.2297372052665-0.229737205266491
2403530.49394792460554.50605207539446
2413532.23558443093662.76441556906341
2423234.0714590501603-2.07145905016035
2432126.6188700603556-5.61887006035564
2442027.5616608286921-7.56166082869212
2453431.03962371192452.96037628807546
2463231.85348298447850.146517015521537
2473434.1909794879922-0.190979487992215
2483233.7349635926304-1.7349635926304
2493334.3146138371325-1.31461383713253
2503333.3540529250894-0.354052925089426
2513734.32857638890042.67142361109964
2523232.5156422466873-0.515642246687265
2533435.1749140097538-1.17491400975384
2543032.2205203585657-2.22052035856572
2553030.9375038056904-0.937503805690408
2563832.83741750624015.16258249375992
2573635.43210762402050.567892375979483
2583230.82281521547051.17718478452953
2593435.5722450624236-1.57224506242363
2603333.8667409558743-0.86674095587434
2612727.1657366265918-0.165736626591792
2623233.4876894551457-1.48768945514570
2633435.9522582876297-1.95225828762967
2642930.8779977961901-1.87799779619012
2653533.31290917166431.68709082833572
2662731.7625560380775-4.76255603807745
2673335.2309047744943-2.23090477449431
2683832.99710699023235.00289300976775
2693634.90576880004151.09423119995850
2703333.9417699081685-0.941769908168503
2713931.85438042681347.1456195731866
2722931.9018723096723-2.9018723096723
2733233.2007741017267-1.20077410172675
2743428.2344852205085.765514779492
2753833.95571947714894.0442805228511
2761725.0831294444403-8.08312944444032
2773534.5995807654250.400419234574966
2783233.9221276148621-1.9221276148621
2793433.5846079016590.415392098340985
2803634.09317658193141.90682341806859
2813135.5254988323898-4.52549883238982
2823534.07884441805470.92115558194532
2832929.5941600765066-0.594160076506555
2842223.9943184072973-1.99431840729729
2854136.24960895467244.75039104532755
2863633.30925512018212.69074487981793
2874238.16769381581663.83230618418341
2883332.23350919247190.766490807528059






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.6717187575269350.6565624849461310.328281242473066
110.5633497623837760.8733004752324480.436650237616224
120.5473512500608710.9052974998782580.452648749939129
130.4251835899122170.8503671798244340.574816410087783
140.4738189237051280.9476378474102560.526181076294872
150.5048159405565590.9903681188868820.495184059443441
160.404479091285550.80895818257110.59552090871445
170.3197367078599300.6394734157198590.68026329214007
180.3870079174958160.7740158349916310.612992082504184
190.4322358327933370.8644716655866740.567764167206663
200.3806731171790540.7613462343581080.619326882820946
210.315209025285750.63041805057150.68479097471425
220.3254070074416430.6508140148832870.674592992558357
230.2690557640201570.5381115280403150.730944235979843
240.2751232669666060.5502465339332110.724876733033394
250.2571338009450690.5142676018901380.742866199054931
260.3919169161058750.783833832211750.608083083894125
270.3429795234911960.6859590469823920.657020476508804
280.3117318584182190.6234637168364380.688268141581781
290.2664659701497860.5329319402995720.733534029850214
300.21601001602170.43202003204340.7839899839783
310.2026340501684550.405268100336910.797365949831545
320.1668790542744600.3337581085489200.83312094572554
330.1672011675705340.3344023351410680.832798832429466
340.156848465128520.313696930257040.84315153487148
350.1615936815887890.3231873631775780.838406318411211
360.1402629989261500.2805259978523010.85973700107385
370.1119845454655300.2239690909310600.88801545453447
380.08749021478108940.1749804295621790.91250978521891
390.07423163669025440.1484632733805090.925768363309746
400.05676701887749140.1135340377549830.943232981122509
410.04658137059934750.0931627411986950.953418629400652
420.0357150296784330.0714300593568660.964284970321567
430.03446982305072180.06893964610144370.965530176949278
440.02542489447549020.05084978895098030.97457510552451
450.07199031073521560.1439806214704310.928009689264784
460.05629930422916490.1125986084583300.943700695770835
470.06807693752643160.1361538750528630.931923062473568
480.05299308703945490.1059861740789100.947006912960545
490.05997682851434580.1199536570286920.940023171485654
500.05210894090550090.1042178818110020.9478910590945
510.05725109151957480.1145021830391500.942748908480425
520.05083643059403120.1016728611880620.949163569405969
530.03954725775955470.07909451551910950.960452742240445
540.03888174861233610.07776349722467220.961118251387664
550.03140386746843810.06280773493687630.968596132531562
560.02525423040021790.05050846080043580.974745769599782
570.02057883807485160.04115767614970320.979421161925148
580.01568532021102920.03137064042205840.98431467978897
590.01404896934585000.02809793869169990.98595103065415
600.01063187529661040.02126375059322070.98936812470339
610.01203382605824950.02406765211649910.98796617394175
620.009080412955267430.01816082591053490.990919587044733
630.006691321429388260.01338264285877650.993308678570612
640.005250490810310110.01050098162062020.99474950918969
650.006038453031810030.01207690606362010.99396154696819
660.005916212936705550.01183242587341110.994083787063294
670.004451445527746910.008902891055493830.995548554472253
680.00859053165558040.01718106331116080.99140946834442
690.01100135532718980.02200271065437970.98899864467281
700.01242704756981590.02485409513963170.987572952430184
710.01126470260612830.02252940521225670.988735297393872
720.01590924125358800.03181848250717610.984090758746412
730.01900275400525210.03800550801050410.980997245994748
740.03559488561887010.07118977123774030.96440511438113
750.07197842604141290.1439568520828260.928021573958587
760.09540554734602470.1908110946920490.904594452653975
770.08127686312908060.1625537262581610.91872313687092
780.08065132504890590.1613026500978120.919348674951094
790.06945258922600090.1389051784520020.930547410774
800.1490232967886810.2980465935773630.850976703211319
810.1451031110313100.2902062220626210.85489688896869
820.1334577175158420.2669154350316840.866542282484158
830.1181344410663460.2362688821326920.881865558933654
840.1002122021099470.2004244042198950.899787797890053
850.09422787836220150.1884557567244030.905772121637798
860.1277320379601400.2554640759202790.87226796203986
870.1087738806487310.2175477612974620.89122611935127
880.09318742470686440.1863748494137290.906812575293136
890.0791778076555440.1583556153110880.920822192344456
900.07838321956679670.1567664391335930.921616780433203
910.085676889282850.17135377856570.91432311071715
920.1348578882170410.2697157764340810.86514211178296
930.1897279510854990.3794559021709980.810272048914501
940.1857184362796670.3714368725593330.814281563720333
950.1636345259035340.3272690518070690.836365474096466
960.1429154421976700.2858308843953390.85708455780233
970.1411771117997780.2823542235995560.858822888200222
980.1232479104117540.2464958208235090.876752089588246
990.1274824211530530.2549648423061060.872517578846947
1000.1098959294535350.2197918589070700.890104070546465
1010.09704434355539820.1940886871107960.902955656444602
1020.0842960483470960.1685920966941920.915703951652904
1030.09890254117372530.1978050823474510.901097458826275
1040.1258005858716330.2516011717432660.874199414128367
1050.1295369015728520.2590738031457040.870463098427148
1060.1140018303245030.2280036606490060.885998169675497
1070.1132037276000490.2264074552000980.886796272399951
1080.1034214482169890.2068428964339790.89657855178301
1090.1429508037481790.2859016074963590.85704919625182
1100.1256423333646290.2512846667292590.87435766663537
1110.1086309269734090.2172618539468180.89136907302659
1120.1994746758671140.3989493517342290.800525324132886
1130.1808199026532620.3616398053065230.819180097346738
1140.1806100232612180.3612200465224370.819389976738782
1150.2352421607803770.4704843215607540.764757839219623
1160.3090727195274490.6181454390548970.690927280472551
1170.283703959251580.567407918503160.71629604074842
1180.2550096954302920.5100193908605840.744990304569708
1190.2731415448821700.5462830897643390.72685845511783
1200.3670698271631760.7341396543263530.632930172836824
1210.3623860284313940.7247720568627870.637613971568606
1220.3429772454861360.6859544909722720.657022754513864
1230.3704944539815970.7409889079631950.629505546018403
1240.3401603629226890.6803207258453790.65983963707731
1250.3452798050278960.6905596100557920.654720194972104
1260.3177501745840180.6355003491680370.682249825415982
1270.3014010529607270.6028021059214550.698598947039273
1280.2814115312518940.5628230625037890.718588468748106
1290.2551853080194290.5103706160388580.744814691980571
1300.2340555419788430.4681110839576850.765944458021157
1310.2105143521932740.4210287043865480.789485647806726
1320.1886231066358600.3772462132717200.81137689336414
1330.1901128083192950.3802256166385890.809887191680705
1340.2156204020408780.4312408040817560.784379597959122
1350.3931539239693390.7863078479386790.60684607603066
1360.3684504291753550.736900858350710.631549570824645
1370.3619317243084680.7238634486169360.638068275691532
1380.3311440416679730.6622880833359460.668855958332027
1390.3326034697586100.6652069395172210.66739653024139
1400.3038305992896280.6076611985792560.696169400710372
1410.3597266721583620.7194533443167240.640273327841638
1420.342659419174480.685318838348960.65734058082552
1430.582489780550790.835020438898420.41751021944921
1440.6359994570267850.7280010859464310.364000542973215
1450.7593012445571560.4813975108856880.240698755442844
1460.7374280467198760.5251439065602470.262571953280124
1470.7338309073244920.5323381853510170.266169092675508
1480.7307021144941750.538595771011650.269297885505825
1490.7299031190100260.5401937619799470.270096880989974
1500.7151829917110730.5696340165778540.284817008288927
1510.7277388620383270.5445222759233450.272261137961673
1520.7405301630245460.5189396739509080.259469836975454
1530.7371662776953930.5256674446092150.262833722304607
1540.736623745984080.5267525080318390.263376254015920
1550.732027538997050.53594492200590.26797246100295
1560.7084521429945640.5830957140108720.291547857005436
1570.7428948295812550.514210340837490.257105170418745
1580.7363991223799870.5272017552400270.263600877620013
1590.7378229281725990.5243541436548020.262177071827401
1600.7572287532611810.4855424934776370.242771246738819
1610.7643892449023280.4712215101953440.235610755097672
1620.8267630705980790.3464738588038420.173236929401921
1630.8162352657924580.3675294684150830.183764734207542
1640.7997007614895630.4005984770208750.200299238510437
1650.8244003970397150.351199205920570.175599602960285
1660.8446485725907410.3107028548185170.155351427409259
1670.8964364373506080.2071271252987840.103563562649392
1680.8962872439671490.2074255120657030.103712756032852
1690.8854928044248640.2290143911502720.114507195575136
1700.8731567961441990.2536864077116030.126843203855801
1710.9022411737297540.1955176525404910.0977588262702455
1720.9367231519748620.1265536960502760.063276848025138
1730.9330309549797010.1339380900405970.0669690450202985
1740.9239816080905480.1520367838189040.076018391909452
1750.9117118732191020.1765762535617960.0882881267808978
1760.8982874682790920.2034250634418150.101712531720908
1770.8879838467435210.2240323065129580.112016153256479
1780.8720878259051340.2558243481897320.127912174094866
1790.8690236426179380.2619527147641240.130976357382062
1800.8669247871584250.2661504256831510.133075212841575
1810.8747068218796410.2505863562407170.125293178120359
1820.8654867894847170.2690264210305660.134513210515283
1830.861677702808510.276644594382980.13832229719149
1840.846917090459570.3061658190808610.153082909540431
1850.8682651202219660.2634697595560680.131734879778034
1860.853154371055680.293691257888640.14684562894432
1870.8704908876831910.2590182246336180.129509112316809
1880.8721101426372610.2557797147254780.127889857362739
1890.8805305454591290.2389389090817430.119469454540871
1900.8634129928688080.2731740142623850.136587007131192
1910.8540625185627730.2918749628744530.145937481437227
1920.8325956232762280.3348087534475440.167404376723772
1930.826758326332840.3464833473343210.173241673667160
1940.8248064837595510.3503870324808980.175193516240449
1950.8285858592133840.3428282815732330.171414140786616
1960.8042800738484510.3914398523030980.195719926151549
1970.7892030542730010.4215938914539980.210796945726999
1980.7690534806808840.4618930386382330.230946519319116
1990.7489913466191760.5020173067616480.251008653380824
2000.7223547489954590.5552905020090830.277645251004541
2010.6918753992515210.6162492014969580.308124600748479
2020.6751552681739520.6496894636520960.324844731826048
2030.6624726274766380.6750547450467250.337527372523362
2040.635988039912760.728023920174480.36401196008724
2050.6042625877205520.7914748245588970.395737412279448
2060.5702028403424140.8595943193151710.429797159657586
2070.5332373212735370.9335253574529260.466762678726463
2080.6877817548752660.6244364902494670.312218245124734
2090.7721603375364360.4556793249271280.227839662463564
2100.741400929830790.5171981403384210.258599070169210
2110.7099793548762050.580041290247590.290020645123795
2120.7687820826339530.4624358347320940.231217917366047
2130.7453226926576930.5093546146846140.254677307342307
2140.723631337495080.5527373250098390.276368662504920
2150.690376526270450.61924694745910.30962347372955
2160.7286275427976180.5427449144047640.271372457202382
2170.6961746782888720.6076506434222550.303825321711128
2180.6610409430022340.6779181139955310.338959056997766
2190.6279202777122340.7441594445755320.372079722287766
2200.5891242500337320.8217514999325360.410875749966268
2210.6702232742204160.6595534515591680.329776725779584
2220.6328156430249540.7343687139500910.367184356975046
2230.5947272397089240.8105455205821530.405272760291076
2240.5544467601829760.8911064796340490.445553239817024
2250.5231286534779640.9537426930440720.476871346522036
2260.5165566738715580.9668866522568840.483443326128442
2270.6144470129748740.7711059740502520.385552987025126
2280.5751467503792570.8497064992414860.424853249620743
2290.6264141186505290.7471717626989420.373585881349471
2300.5883829555805820.8232340888388370.411617044419418
2310.5757963884125020.8484072231749960.424203611587498
2320.5558145580032540.8883708839934920.444185441996746
2330.7421820718886840.5156358562226320.257817928111316
2340.7054025336073650.589194932785270.294597466392635
2350.755666289325120.4886674213497620.244333710674881
2360.742384690798980.5152306184020410.257615309201021
2370.7049204167160480.5901591665679030.295079583283952
2380.6737847940909430.6524304118181130.326215205909057
2390.64337224797260.71325550405480.3566277520274
2400.6787131455501820.6425737088996360.321286854449818
2410.6570475317638170.6859049364723660.342952468236183
2420.6237867293318780.7524265413362440.376213270668122
2430.6318061401488620.7363877197022750.368193859851138
2440.733249304122450.5335013917550990.266750695877549
2450.7247891754008540.5504216491982910.275210824599146
2460.6796396230678380.6407207538643250.320360376932162
2470.6312706235248040.7374587529503930.368729376475196
2480.5937365682012950.812526863597410.406263431798705
2490.5618586072737320.8762827854525360.438141392726268
2500.5131291830774590.9737416338450820.486870816922541
2510.4727336050670910.9454672101341830.527266394932909
2520.4195035685269870.8390071370539750.580496431473013
2530.3705428775662410.7410857551324830.629457122433759
2540.3504502149261650.700900429852330.649549785073835
2550.2997261962018520.5994523924037040.700273803798148
2560.4092567870750110.8185135741500220.590743212924989
2570.3781753772722450.756350754544490.621824622727755
2580.3318035751116510.6636071502233020.668196424888349
2590.3353984627948480.6707969255896970.664601537205152
2600.3195776332140430.6391552664280860.680422366785957
2610.304496481899310.608992963798620.69550351810069
2620.2856770358058280.5713540716116550.714322964194172
2630.2975964888280740.5951929776561480.702403511171926
2640.3457054530600860.6914109061201730.654294546939914
2650.2964378235691510.5928756471383030.703562176430849
2660.4387659840479170.8775319680958350.561234015952083
2670.6791573507053240.6416852985893530.320842649294676
2680.6111033713223690.7777932573552630.388896628677631
2690.5342773926853410.9314452146293180.465722607314659
2700.4661670530508280.9323341061016560.533832946949172
2710.4274345305297170.8548690610594340.572565469470283
2720.7034574594779890.5930850810440220.296542540522011
2730.6060017399195870.7879965201608260.393998260080413
2740.5303373663559950.939325267288010.469662633644005
2750.4456181590395430.8912363180790870.554381840960457
2760.6291509521953230.7416980956093530.370849047804677
2770.5473230932046220.9053538135907560.452676906795378
2780.3925191425723110.7850382851446220.607480857427689

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.671718757526935 & 0.656562484946131 & 0.328281242473066 \tabularnewline
11 & 0.563349762383776 & 0.873300475232448 & 0.436650237616224 \tabularnewline
12 & 0.547351250060871 & 0.905297499878258 & 0.452648749939129 \tabularnewline
13 & 0.425183589912217 & 0.850367179824434 & 0.574816410087783 \tabularnewline
14 & 0.473818923705128 & 0.947637847410256 & 0.526181076294872 \tabularnewline
15 & 0.504815940556559 & 0.990368118886882 & 0.495184059443441 \tabularnewline
16 & 0.40447909128555 & 0.8089581825711 & 0.59552090871445 \tabularnewline
17 & 0.319736707859930 & 0.639473415719859 & 0.68026329214007 \tabularnewline
18 & 0.387007917495816 & 0.774015834991631 & 0.612992082504184 \tabularnewline
19 & 0.432235832793337 & 0.864471665586674 & 0.567764167206663 \tabularnewline
20 & 0.380673117179054 & 0.761346234358108 & 0.619326882820946 \tabularnewline
21 & 0.31520902528575 & 0.6304180505715 & 0.68479097471425 \tabularnewline
22 & 0.325407007441643 & 0.650814014883287 & 0.674592992558357 \tabularnewline
23 & 0.269055764020157 & 0.538111528040315 & 0.730944235979843 \tabularnewline
24 & 0.275123266966606 & 0.550246533933211 & 0.724876733033394 \tabularnewline
25 & 0.257133800945069 & 0.514267601890138 & 0.742866199054931 \tabularnewline
26 & 0.391916916105875 & 0.78383383221175 & 0.608083083894125 \tabularnewline
27 & 0.342979523491196 & 0.685959046982392 & 0.657020476508804 \tabularnewline
28 & 0.311731858418219 & 0.623463716836438 & 0.688268141581781 \tabularnewline
29 & 0.266465970149786 & 0.532931940299572 & 0.733534029850214 \tabularnewline
30 & 0.2160100160217 & 0.4320200320434 & 0.7839899839783 \tabularnewline
31 & 0.202634050168455 & 0.40526810033691 & 0.797365949831545 \tabularnewline
32 & 0.166879054274460 & 0.333758108548920 & 0.83312094572554 \tabularnewline
33 & 0.167201167570534 & 0.334402335141068 & 0.832798832429466 \tabularnewline
34 & 0.15684846512852 & 0.31369693025704 & 0.84315153487148 \tabularnewline
35 & 0.161593681588789 & 0.323187363177578 & 0.838406318411211 \tabularnewline
36 & 0.140262998926150 & 0.280525997852301 & 0.85973700107385 \tabularnewline
37 & 0.111984545465530 & 0.223969090931060 & 0.88801545453447 \tabularnewline
38 & 0.0874902147810894 & 0.174980429562179 & 0.91250978521891 \tabularnewline
39 & 0.0742316366902544 & 0.148463273380509 & 0.925768363309746 \tabularnewline
40 & 0.0567670188774914 & 0.113534037754983 & 0.943232981122509 \tabularnewline
41 & 0.0465813705993475 & 0.093162741198695 & 0.953418629400652 \tabularnewline
42 & 0.035715029678433 & 0.071430059356866 & 0.964284970321567 \tabularnewline
43 & 0.0344698230507218 & 0.0689396461014437 & 0.965530176949278 \tabularnewline
44 & 0.0254248944754902 & 0.0508497889509803 & 0.97457510552451 \tabularnewline
45 & 0.0719903107352156 & 0.143980621470431 & 0.928009689264784 \tabularnewline
46 & 0.0562993042291649 & 0.112598608458330 & 0.943700695770835 \tabularnewline
47 & 0.0680769375264316 & 0.136153875052863 & 0.931923062473568 \tabularnewline
48 & 0.0529930870394549 & 0.105986174078910 & 0.947006912960545 \tabularnewline
49 & 0.0599768285143458 & 0.119953657028692 & 0.940023171485654 \tabularnewline
50 & 0.0521089409055009 & 0.104217881811002 & 0.9478910590945 \tabularnewline
51 & 0.0572510915195748 & 0.114502183039150 & 0.942748908480425 \tabularnewline
52 & 0.0508364305940312 & 0.101672861188062 & 0.949163569405969 \tabularnewline
53 & 0.0395472577595547 & 0.0790945155191095 & 0.960452742240445 \tabularnewline
54 & 0.0388817486123361 & 0.0777634972246722 & 0.961118251387664 \tabularnewline
55 & 0.0314038674684381 & 0.0628077349368763 & 0.968596132531562 \tabularnewline
56 & 0.0252542304002179 & 0.0505084608004358 & 0.974745769599782 \tabularnewline
57 & 0.0205788380748516 & 0.0411576761497032 & 0.979421161925148 \tabularnewline
58 & 0.0156853202110292 & 0.0313706404220584 & 0.98431467978897 \tabularnewline
59 & 0.0140489693458500 & 0.0280979386916999 & 0.98595103065415 \tabularnewline
60 & 0.0106318752966104 & 0.0212637505932207 & 0.98936812470339 \tabularnewline
61 & 0.0120338260582495 & 0.0240676521164991 & 0.98796617394175 \tabularnewline
62 & 0.00908041295526743 & 0.0181608259105349 & 0.990919587044733 \tabularnewline
63 & 0.00669132142938826 & 0.0133826428587765 & 0.993308678570612 \tabularnewline
64 & 0.00525049081031011 & 0.0105009816206202 & 0.99474950918969 \tabularnewline
65 & 0.00603845303181003 & 0.0120769060636201 & 0.99396154696819 \tabularnewline
66 & 0.00591621293670555 & 0.0118324258734111 & 0.994083787063294 \tabularnewline
67 & 0.00445144552774691 & 0.00890289105549383 & 0.995548554472253 \tabularnewline
68 & 0.0085905316555804 & 0.0171810633111608 & 0.99140946834442 \tabularnewline
69 & 0.0110013553271898 & 0.0220027106543797 & 0.98899864467281 \tabularnewline
70 & 0.0124270475698159 & 0.0248540951396317 & 0.987572952430184 \tabularnewline
71 & 0.0112647026061283 & 0.0225294052122567 & 0.988735297393872 \tabularnewline
72 & 0.0159092412535880 & 0.0318184825071761 & 0.984090758746412 \tabularnewline
73 & 0.0190027540052521 & 0.0380055080105041 & 0.980997245994748 \tabularnewline
74 & 0.0355948856188701 & 0.0711897712377403 & 0.96440511438113 \tabularnewline
75 & 0.0719784260414129 & 0.143956852082826 & 0.928021573958587 \tabularnewline
76 & 0.0954055473460247 & 0.190811094692049 & 0.904594452653975 \tabularnewline
77 & 0.0812768631290806 & 0.162553726258161 & 0.91872313687092 \tabularnewline
78 & 0.0806513250489059 & 0.161302650097812 & 0.919348674951094 \tabularnewline
79 & 0.0694525892260009 & 0.138905178452002 & 0.930547410774 \tabularnewline
80 & 0.149023296788681 & 0.298046593577363 & 0.850976703211319 \tabularnewline
81 & 0.145103111031310 & 0.290206222062621 & 0.85489688896869 \tabularnewline
82 & 0.133457717515842 & 0.266915435031684 & 0.866542282484158 \tabularnewline
83 & 0.118134441066346 & 0.236268882132692 & 0.881865558933654 \tabularnewline
84 & 0.100212202109947 & 0.200424404219895 & 0.899787797890053 \tabularnewline
85 & 0.0942278783622015 & 0.188455756724403 & 0.905772121637798 \tabularnewline
86 & 0.127732037960140 & 0.255464075920279 & 0.87226796203986 \tabularnewline
87 & 0.108773880648731 & 0.217547761297462 & 0.89122611935127 \tabularnewline
88 & 0.0931874247068644 & 0.186374849413729 & 0.906812575293136 \tabularnewline
89 & 0.079177807655544 & 0.158355615311088 & 0.920822192344456 \tabularnewline
90 & 0.0783832195667967 & 0.156766439133593 & 0.921616780433203 \tabularnewline
91 & 0.08567688928285 & 0.1713537785657 & 0.91432311071715 \tabularnewline
92 & 0.134857888217041 & 0.269715776434081 & 0.86514211178296 \tabularnewline
93 & 0.189727951085499 & 0.379455902170998 & 0.810272048914501 \tabularnewline
94 & 0.185718436279667 & 0.371436872559333 & 0.814281563720333 \tabularnewline
95 & 0.163634525903534 & 0.327269051807069 & 0.836365474096466 \tabularnewline
96 & 0.142915442197670 & 0.285830884395339 & 0.85708455780233 \tabularnewline
97 & 0.141177111799778 & 0.282354223599556 & 0.858822888200222 \tabularnewline
98 & 0.123247910411754 & 0.246495820823509 & 0.876752089588246 \tabularnewline
99 & 0.127482421153053 & 0.254964842306106 & 0.872517578846947 \tabularnewline
100 & 0.109895929453535 & 0.219791858907070 & 0.890104070546465 \tabularnewline
101 & 0.0970443435553982 & 0.194088687110796 & 0.902955656444602 \tabularnewline
102 & 0.084296048347096 & 0.168592096694192 & 0.915703951652904 \tabularnewline
103 & 0.0989025411737253 & 0.197805082347451 & 0.901097458826275 \tabularnewline
104 & 0.125800585871633 & 0.251601171743266 & 0.874199414128367 \tabularnewline
105 & 0.129536901572852 & 0.259073803145704 & 0.870463098427148 \tabularnewline
106 & 0.114001830324503 & 0.228003660649006 & 0.885998169675497 \tabularnewline
107 & 0.113203727600049 & 0.226407455200098 & 0.886796272399951 \tabularnewline
108 & 0.103421448216989 & 0.206842896433979 & 0.89657855178301 \tabularnewline
109 & 0.142950803748179 & 0.285901607496359 & 0.85704919625182 \tabularnewline
110 & 0.125642333364629 & 0.251284666729259 & 0.87435766663537 \tabularnewline
111 & 0.108630926973409 & 0.217261853946818 & 0.89136907302659 \tabularnewline
112 & 0.199474675867114 & 0.398949351734229 & 0.800525324132886 \tabularnewline
113 & 0.180819902653262 & 0.361639805306523 & 0.819180097346738 \tabularnewline
114 & 0.180610023261218 & 0.361220046522437 & 0.819389976738782 \tabularnewline
115 & 0.235242160780377 & 0.470484321560754 & 0.764757839219623 \tabularnewline
116 & 0.309072719527449 & 0.618145439054897 & 0.690927280472551 \tabularnewline
117 & 0.28370395925158 & 0.56740791850316 & 0.71629604074842 \tabularnewline
118 & 0.255009695430292 & 0.510019390860584 & 0.744990304569708 \tabularnewline
119 & 0.273141544882170 & 0.546283089764339 & 0.72685845511783 \tabularnewline
120 & 0.367069827163176 & 0.734139654326353 & 0.632930172836824 \tabularnewline
121 & 0.362386028431394 & 0.724772056862787 & 0.637613971568606 \tabularnewline
122 & 0.342977245486136 & 0.685954490972272 & 0.657022754513864 \tabularnewline
123 & 0.370494453981597 & 0.740988907963195 & 0.629505546018403 \tabularnewline
124 & 0.340160362922689 & 0.680320725845379 & 0.65983963707731 \tabularnewline
125 & 0.345279805027896 & 0.690559610055792 & 0.654720194972104 \tabularnewline
126 & 0.317750174584018 & 0.635500349168037 & 0.682249825415982 \tabularnewline
127 & 0.301401052960727 & 0.602802105921455 & 0.698598947039273 \tabularnewline
128 & 0.281411531251894 & 0.562823062503789 & 0.718588468748106 \tabularnewline
129 & 0.255185308019429 & 0.510370616038858 & 0.744814691980571 \tabularnewline
130 & 0.234055541978843 & 0.468111083957685 & 0.765944458021157 \tabularnewline
131 & 0.210514352193274 & 0.421028704386548 & 0.789485647806726 \tabularnewline
132 & 0.188623106635860 & 0.377246213271720 & 0.81137689336414 \tabularnewline
133 & 0.190112808319295 & 0.380225616638589 & 0.809887191680705 \tabularnewline
134 & 0.215620402040878 & 0.431240804081756 & 0.784379597959122 \tabularnewline
135 & 0.393153923969339 & 0.786307847938679 & 0.60684607603066 \tabularnewline
136 & 0.368450429175355 & 0.73690085835071 & 0.631549570824645 \tabularnewline
137 & 0.361931724308468 & 0.723863448616936 & 0.638068275691532 \tabularnewline
138 & 0.331144041667973 & 0.662288083335946 & 0.668855958332027 \tabularnewline
139 & 0.332603469758610 & 0.665206939517221 & 0.66739653024139 \tabularnewline
140 & 0.303830599289628 & 0.607661198579256 & 0.696169400710372 \tabularnewline
141 & 0.359726672158362 & 0.719453344316724 & 0.640273327841638 \tabularnewline
142 & 0.34265941917448 & 0.68531883834896 & 0.65734058082552 \tabularnewline
143 & 0.58248978055079 & 0.83502043889842 & 0.41751021944921 \tabularnewline
144 & 0.635999457026785 & 0.728001085946431 & 0.364000542973215 \tabularnewline
145 & 0.759301244557156 & 0.481397510885688 & 0.240698755442844 \tabularnewline
146 & 0.737428046719876 & 0.525143906560247 & 0.262571953280124 \tabularnewline
147 & 0.733830907324492 & 0.532338185351017 & 0.266169092675508 \tabularnewline
148 & 0.730702114494175 & 0.53859577101165 & 0.269297885505825 \tabularnewline
149 & 0.729903119010026 & 0.540193761979947 & 0.270096880989974 \tabularnewline
150 & 0.715182991711073 & 0.569634016577854 & 0.284817008288927 \tabularnewline
151 & 0.727738862038327 & 0.544522275923345 & 0.272261137961673 \tabularnewline
152 & 0.740530163024546 & 0.518939673950908 & 0.259469836975454 \tabularnewline
153 & 0.737166277695393 & 0.525667444609215 & 0.262833722304607 \tabularnewline
154 & 0.73662374598408 & 0.526752508031839 & 0.263376254015920 \tabularnewline
155 & 0.73202753899705 & 0.5359449220059 & 0.26797246100295 \tabularnewline
156 & 0.708452142994564 & 0.583095714010872 & 0.291547857005436 \tabularnewline
157 & 0.742894829581255 & 0.51421034083749 & 0.257105170418745 \tabularnewline
158 & 0.736399122379987 & 0.527201755240027 & 0.263600877620013 \tabularnewline
159 & 0.737822928172599 & 0.524354143654802 & 0.262177071827401 \tabularnewline
160 & 0.757228753261181 & 0.485542493477637 & 0.242771246738819 \tabularnewline
161 & 0.764389244902328 & 0.471221510195344 & 0.235610755097672 \tabularnewline
162 & 0.826763070598079 & 0.346473858803842 & 0.173236929401921 \tabularnewline
163 & 0.816235265792458 & 0.367529468415083 & 0.183764734207542 \tabularnewline
164 & 0.799700761489563 & 0.400598477020875 & 0.200299238510437 \tabularnewline
165 & 0.824400397039715 & 0.35119920592057 & 0.175599602960285 \tabularnewline
166 & 0.844648572590741 & 0.310702854818517 & 0.155351427409259 \tabularnewline
167 & 0.896436437350608 & 0.207127125298784 & 0.103563562649392 \tabularnewline
168 & 0.896287243967149 & 0.207425512065703 & 0.103712756032852 \tabularnewline
169 & 0.885492804424864 & 0.229014391150272 & 0.114507195575136 \tabularnewline
170 & 0.873156796144199 & 0.253686407711603 & 0.126843203855801 \tabularnewline
171 & 0.902241173729754 & 0.195517652540491 & 0.0977588262702455 \tabularnewline
172 & 0.936723151974862 & 0.126553696050276 & 0.063276848025138 \tabularnewline
173 & 0.933030954979701 & 0.133938090040597 & 0.0669690450202985 \tabularnewline
174 & 0.923981608090548 & 0.152036783818904 & 0.076018391909452 \tabularnewline
175 & 0.911711873219102 & 0.176576253561796 & 0.0882881267808978 \tabularnewline
176 & 0.898287468279092 & 0.203425063441815 & 0.101712531720908 \tabularnewline
177 & 0.887983846743521 & 0.224032306512958 & 0.112016153256479 \tabularnewline
178 & 0.872087825905134 & 0.255824348189732 & 0.127912174094866 \tabularnewline
179 & 0.869023642617938 & 0.261952714764124 & 0.130976357382062 \tabularnewline
180 & 0.866924787158425 & 0.266150425683151 & 0.133075212841575 \tabularnewline
181 & 0.874706821879641 & 0.250586356240717 & 0.125293178120359 \tabularnewline
182 & 0.865486789484717 & 0.269026421030566 & 0.134513210515283 \tabularnewline
183 & 0.86167770280851 & 0.27664459438298 & 0.13832229719149 \tabularnewline
184 & 0.84691709045957 & 0.306165819080861 & 0.153082909540431 \tabularnewline
185 & 0.868265120221966 & 0.263469759556068 & 0.131734879778034 \tabularnewline
186 & 0.85315437105568 & 0.29369125788864 & 0.14684562894432 \tabularnewline
187 & 0.870490887683191 & 0.259018224633618 & 0.129509112316809 \tabularnewline
188 & 0.872110142637261 & 0.255779714725478 & 0.127889857362739 \tabularnewline
189 & 0.880530545459129 & 0.238938909081743 & 0.119469454540871 \tabularnewline
190 & 0.863412992868808 & 0.273174014262385 & 0.136587007131192 \tabularnewline
191 & 0.854062518562773 & 0.291874962874453 & 0.145937481437227 \tabularnewline
192 & 0.832595623276228 & 0.334808753447544 & 0.167404376723772 \tabularnewline
193 & 0.82675832633284 & 0.346483347334321 & 0.173241673667160 \tabularnewline
194 & 0.824806483759551 & 0.350387032480898 & 0.175193516240449 \tabularnewline
195 & 0.828585859213384 & 0.342828281573233 & 0.171414140786616 \tabularnewline
196 & 0.804280073848451 & 0.391439852303098 & 0.195719926151549 \tabularnewline
197 & 0.789203054273001 & 0.421593891453998 & 0.210796945726999 \tabularnewline
198 & 0.769053480680884 & 0.461893038638233 & 0.230946519319116 \tabularnewline
199 & 0.748991346619176 & 0.502017306761648 & 0.251008653380824 \tabularnewline
200 & 0.722354748995459 & 0.555290502009083 & 0.277645251004541 \tabularnewline
201 & 0.691875399251521 & 0.616249201496958 & 0.308124600748479 \tabularnewline
202 & 0.675155268173952 & 0.649689463652096 & 0.324844731826048 \tabularnewline
203 & 0.662472627476638 & 0.675054745046725 & 0.337527372523362 \tabularnewline
204 & 0.63598803991276 & 0.72802392017448 & 0.36401196008724 \tabularnewline
205 & 0.604262587720552 & 0.791474824558897 & 0.395737412279448 \tabularnewline
206 & 0.570202840342414 & 0.859594319315171 & 0.429797159657586 \tabularnewline
207 & 0.533237321273537 & 0.933525357452926 & 0.466762678726463 \tabularnewline
208 & 0.687781754875266 & 0.624436490249467 & 0.312218245124734 \tabularnewline
209 & 0.772160337536436 & 0.455679324927128 & 0.227839662463564 \tabularnewline
210 & 0.74140092983079 & 0.517198140338421 & 0.258599070169210 \tabularnewline
211 & 0.709979354876205 & 0.58004129024759 & 0.290020645123795 \tabularnewline
212 & 0.768782082633953 & 0.462435834732094 & 0.231217917366047 \tabularnewline
213 & 0.745322692657693 & 0.509354614684614 & 0.254677307342307 \tabularnewline
214 & 0.72363133749508 & 0.552737325009839 & 0.276368662504920 \tabularnewline
215 & 0.69037652627045 & 0.6192469474591 & 0.30962347372955 \tabularnewline
216 & 0.728627542797618 & 0.542744914404764 & 0.271372457202382 \tabularnewline
217 & 0.696174678288872 & 0.607650643422255 & 0.303825321711128 \tabularnewline
218 & 0.661040943002234 & 0.677918113995531 & 0.338959056997766 \tabularnewline
219 & 0.627920277712234 & 0.744159444575532 & 0.372079722287766 \tabularnewline
220 & 0.589124250033732 & 0.821751499932536 & 0.410875749966268 \tabularnewline
221 & 0.670223274220416 & 0.659553451559168 & 0.329776725779584 \tabularnewline
222 & 0.632815643024954 & 0.734368713950091 & 0.367184356975046 \tabularnewline
223 & 0.594727239708924 & 0.810545520582153 & 0.405272760291076 \tabularnewline
224 & 0.554446760182976 & 0.891106479634049 & 0.445553239817024 \tabularnewline
225 & 0.523128653477964 & 0.953742693044072 & 0.476871346522036 \tabularnewline
226 & 0.516556673871558 & 0.966886652256884 & 0.483443326128442 \tabularnewline
227 & 0.614447012974874 & 0.771105974050252 & 0.385552987025126 \tabularnewline
228 & 0.575146750379257 & 0.849706499241486 & 0.424853249620743 \tabularnewline
229 & 0.626414118650529 & 0.747171762698942 & 0.373585881349471 \tabularnewline
230 & 0.588382955580582 & 0.823234088838837 & 0.411617044419418 \tabularnewline
231 & 0.575796388412502 & 0.848407223174996 & 0.424203611587498 \tabularnewline
232 & 0.555814558003254 & 0.888370883993492 & 0.444185441996746 \tabularnewline
233 & 0.742182071888684 & 0.515635856222632 & 0.257817928111316 \tabularnewline
234 & 0.705402533607365 & 0.58919493278527 & 0.294597466392635 \tabularnewline
235 & 0.75566628932512 & 0.488667421349762 & 0.244333710674881 \tabularnewline
236 & 0.74238469079898 & 0.515230618402041 & 0.257615309201021 \tabularnewline
237 & 0.704920416716048 & 0.590159166567903 & 0.295079583283952 \tabularnewline
238 & 0.673784794090943 & 0.652430411818113 & 0.326215205909057 \tabularnewline
239 & 0.6433722479726 & 0.7132555040548 & 0.3566277520274 \tabularnewline
240 & 0.678713145550182 & 0.642573708899636 & 0.321286854449818 \tabularnewline
241 & 0.657047531763817 & 0.685904936472366 & 0.342952468236183 \tabularnewline
242 & 0.623786729331878 & 0.752426541336244 & 0.376213270668122 \tabularnewline
243 & 0.631806140148862 & 0.736387719702275 & 0.368193859851138 \tabularnewline
244 & 0.73324930412245 & 0.533501391755099 & 0.266750695877549 \tabularnewline
245 & 0.724789175400854 & 0.550421649198291 & 0.275210824599146 \tabularnewline
246 & 0.679639623067838 & 0.640720753864325 & 0.320360376932162 \tabularnewline
247 & 0.631270623524804 & 0.737458752950393 & 0.368729376475196 \tabularnewline
248 & 0.593736568201295 & 0.81252686359741 & 0.406263431798705 \tabularnewline
249 & 0.561858607273732 & 0.876282785452536 & 0.438141392726268 \tabularnewline
250 & 0.513129183077459 & 0.973741633845082 & 0.486870816922541 \tabularnewline
251 & 0.472733605067091 & 0.945467210134183 & 0.527266394932909 \tabularnewline
252 & 0.419503568526987 & 0.839007137053975 & 0.580496431473013 \tabularnewline
253 & 0.370542877566241 & 0.741085755132483 & 0.629457122433759 \tabularnewline
254 & 0.350450214926165 & 0.70090042985233 & 0.649549785073835 \tabularnewline
255 & 0.299726196201852 & 0.599452392403704 & 0.700273803798148 \tabularnewline
256 & 0.409256787075011 & 0.818513574150022 & 0.590743212924989 \tabularnewline
257 & 0.378175377272245 & 0.75635075454449 & 0.621824622727755 \tabularnewline
258 & 0.331803575111651 & 0.663607150223302 & 0.668196424888349 \tabularnewline
259 & 0.335398462794848 & 0.670796925589697 & 0.664601537205152 \tabularnewline
260 & 0.319577633214043 & 0.639155266428086 & 0.680422366785957 \tabularnewline
261 & 0.30449648189931 & 0.60899296379862 & 0.69550351810069 \tabularnewline
262 & 0.285677035805828 & 0.571354071611655 & 0.714322964194172 \tabularnewline
263 & 0.297596488828074 & 0.595192977656148 & 0.702403511171926 \tabularnewline
264 & 0.345705453060086 & 0.691410906120173 & 0.654294546939914 \tabularnewline
265 & 0.296437823569151 & 0.592875647138303 & 0.703562176430849 \tabularnewline
266 & 0.438765984047917 & 0.877531968095835 & 0.561234015952083 \tabularnewline
267 & 0.679157350705324 & 0.641685298589353 & 0.320842649294676 \tabularnewline
268 & 0.611103371322369 & 0.777793257355263 & 0.388896628677631 \tabularnewline
269 & 0.534277392685341 & 0.931445214629318 & 0.465722607314659 \tabularnewline
270 & 0.466167053050828 & 0.932334106101656 & 0.533832946949172 \tabularnewline
271 & 0.427434530529717 & 0.854869061059434 & 0.572565469470283 \tabularnewline
272 & 0.703457459477989 & 0.593085081044022 & 0.296542540522011 \tabularnewline
273 & 0.606001739919587 & 0.787996520160826 & 0.393998260080413 \tabularnewline
274 & 0.530337366355995 & 0.93932526728801 & 0.469662633644005 \tabularnewline
275 & 0.445618159039543 & 0.891236318079087 & 0.554381840960457 \tabularnewline
276 & 0.629150952195323 & 0.741698095609353 & 0.370849047804677 \tabularnewline
277 & 0.547323093204622 & 0.905353813590756 & 0.452676906795378 \tabularnewline
278 & 0.392519142572311 & 0.785038285144622 & 0.607480857427689 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113583&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]10[/C][C]0.671718757526935[/C][C]0.656562484946131[/C][C]0.328281242473066[/C][/ROW]
[ROW][C]11[/C][C]0.563349762383776[/C][C]0.873300475232448[/C][C]0.436650237616224[/C][/ROW]
[ROW][C]12[/C][C]0.547351250060871[/C][C]0.905297499878258[/C][C]0.452648749939129[/C][/ROW]
[ROW][C]13[/C][C]0.425183589912217[/C][C]0.850367179824434[/C][C]0.574816410087783[/C][/ROW]
[ROW][C]14[/C][C]0.473818923705128[/C][C]0.947637847410256[/C][C]0.526181076294872[/C][/ROW]
[ROW][C]15[/C][C]0.504815940556559[/C][C]0.990368118886882[/C][C]0.495184059443441[/C][/ROW]
[ROW][C]16[/C][C]0.40447909128555[/C][C]0.8089581825711[/C][C]0.59552090871445[/C][/ROW]
[ROW][C]17[/C][C]0.319736707859930[/C][C]0.639473415719859[/C][C]0.68026329214007[/C][/ROW]
[ROW][C]18[/C][C]0.387007917495816[/C][C]0.774015834991631[/C][C]0.612992082504184[/C][/ROW]
[ROW][C]19[/C][C]0.432235832793337[/C][C]0.864471665586674[/C][C]0.567764167206663[/C][/ROW]
[ROW][C]20[/C][C]0.380673117179054[/C][C]0.761346234358108[/C][C]0.619326882820946[/C][/ROW]
[ROW][C]21[/C][C]0.31520902528575[/C][C]0.6304180505715[/C][C]0.68479097471425[/C][/ROW]
[ROW][C]22[/C][C]0.325407007441643[/C][C]0.650814014883287[/C][C]0.674592992558357[/C][/ROW]
[ROW][C]23[/C][C]0.269055764020157[/C][C]0.538111528040315[/C][C]0.730944235979843[/C][/ROW]
[ROW][C]24[/C][C]0.275123266966606[/C][C]0.550246533933211[/C][C]0.724876733033394[/C][/ROW]
[ROW][C]25[/C][C]0.257133800945069[/C][C]0.514267601890138[/C][C]0.742866199054931[/C][/ROW]
[ROW][C]26[/C][C]0.391916916105875[/C][C]0.78383383221175[/C][C]0.608083083894125[/C][/ROW]
[ROW][C]27[/C][C]0.342979523491196[/C][C]0.685959046982392[/C][C]0.657020476508804[/C][/ROW]
[ROW][C]28[/C][C]0.311731858418219[/C][C]0.623463716836438[/C][C]0.688268141581781[/C][/ROW]
[ROW][C]29[/C][C]0.266465970149786[/C][C]0.532931940299572[/C][C]0.733534029850214[/C][/ROW]
[ROW][C]30[/C][C]0.2160100160217[/C][C]0.4320200320434[/C][C]0.7839899839783[/C][/ROW]
[ROW][C]31[/C][C]0.202634050168455[/C][C]0.40526810033691[/C][C]0.797365949831545[/C][/ROW]
[ROW][C]32[/C][C]0.166879054274460[/C][C]0.333758108548920[/C][C]0.83312094572554[/C][/ROW]
[ROW][C]33[/C][C]0.167201167570534[/C][C]0.334402335141068[/C][C]0.832798832429466[/C][/ROW]
[ROW][C]34[/C][C]0.15684846512852[/C][C]0.31369693025704[/C][C]0.84315153487148[/C][/ROW]
[ROW][C]35[/C][C]0.161593681588789[/C][C]0.323187363177578[/C][C]0.838406318411211[/C][/ROW]
[ROW][C]36[/C][C]0.140262998926150[/C][C]0.280525997852301[/C][C]0.85973700107385[/C][/ROW]
[ROW][C]37[/C][C]0.111984545465530[/C][C]0.223969090931060[/C][C]0.88801545453447[/C][/ROW]
[ROW][C]38[/C][C]0.0874902147810894[/C][C]0.174980429562179[/C][C]0.91250978521891[/C][/ROW]
[ROW][C]39[/C][C]0.0742316366902544[/C][C]0.148463273380509[/C][C]0.925768363309746[/C][/ROW]
[ROW][C]40[/C][C]0.0567670188774914[/C][C]0.113534037754983[/C][C]0.943232981122509[/C][/ROW]
[ROW][C]41[/C][C]0.0465813705993475[/C][C]0.093162741198695[/C][C]0.953418629400652[/C][/ROW]
[ROW][C]42[/C][C]0.035715029678433[/C][C]0.071430059356866[/C][C]0.964284970321567[/C][/ROW]
[ROW][C]43[/C][C]0.0344698230507218[/C][C]0.0689396461014437[/C][C]0.965530176949278[/C][/ROW]
[ROW][C]44[/C][C]0.0254248944754902[/C][C]0.0508497889509803[/C][C]0.97457510552451[/C][/ROW]
[ROW][C]45[/C][C]0.0719903107352156[/C][C]0.143980621470431[/C][C]0.928009689264784[/C][/ROW]
[ROW][C]46[/C][C]0.0562993042291649[/C][C]0.112598608458330[/C][C]0.943700695770835[/C][/ROW]
[ROW][C]47[/C][C]0.0680769375264316[/C][C]0.136153875052863[/C][C]0.931923062473568[/C][/ROW]
[ROW][C]48[/C][C]0.0529930870394549[/C][C]0.105986174078910[/C][C]0.947006912960545[/C][/ROW]
[ROW][C]49[/C][C]0.0599768285143458[/C][C]0.119953657028692[/C][C]0.940023171485654[/C][/ROW]
[ROW][C]50[/C][C]0.0521089409055009[/C][C]0.104217881811002[/C][C]0.9478910590945[/C][/ROW]
[ROW][C]51[/C][C]0.0572510915195748[/C][C]0.114502183039150[/C][C]0.942748908480425[/C][/ROW]
[ROW][C]52[/C][C]0.0508364305940312[/C][C]0.101672861188062[/C][C]0.949163569405969[/C][/ROW]
[ROW][C]53[/C][C]0.0395472577595547[/C][C]0.0790945155191095[/C][C]0.960452742240445[/C][/ROW]
[ROW][C]54[/C][C]0.0388817486123361[/C][C]0.0777634972246722[/C][C]0.961118251387664[/C][/ROW]
[ROW][C]55[/C][C]0.0314038674684381[/C][C]0.0628077349368763[/C][C]0.968596132531562[/C][/ROW]
[ROW][C]56[/C][C]0.0252542304002179[/C][C]0.0505084608004358[/C][C]0.974745769599782[/C][/ROW]
[ROW][C]57[/C][C]0.0205788380748516[/C][C]0.0411576761497032[/C][C]0.979421161925148[/C][/ROW]
[ROW][C]58[/C][C]0.0156853202110292[/C][C]0.0313706404220584[/C][C]0.98431467978897[/C][/ROW]
[ROW][C]59[/C][C]0.0140489693458500[/C][C]0.0280979386916999[/C][C]0.98595103065415[/C][/ROW]
[ROW][C]60[/C][C]0.0106318752966104[/C][C]0.0212637505932207[/C][C]0.98936812470339[/C][/ROW]
[ROW][C]61[/C][C]0.0120338260582495[/C][C]0.0240676521164991[/C][C]0.98796617394175[/C][/ROW]
[ROW][C]62[/C][C]0.00908041295526743[/C][C]0.0181608259105349[/C][C]0.990919587044733[/C][/ROW]
[ROW][C]63[/C][C]0.00669132142938826[/C][C]0.0133826428587765[/C][C]0.993308678570612[/C][/ROW]
[ROW][C]64[/C][C]0.00525049081031011[/C][C]0.0105009816206202[/C][C]0.99474950918969[/C][/ROW]
[ROW][C]65[/C][C]0.00603845303181003[/C][C]0.0120769060636201[/C][C]0.99396154696819[/C][/ROW]
[ROW][C]66[/C][C]0.00591621293670555[/C][C]0.0118324258734111[/C][C]0.994083787063294[/C][/ROW]
[ROW][C]67[/C][C]0.00445144552774691[/C][C]0.00890289105549383[/C][C]0.995548554472253[/C][/ROW]
[ROW][C]68[/C][C]0.0085905316555804[/C][C]0.0171810633111608[/C][C]0.99140946834442[/C][/ROW]
[ROW][C]69[/C][C]0.0110013553271898[/C][C]0.0220027106543797[/C][C]0.98899864467281[/C][/ROW]
[ROW][C]70[/C][C]0.0124270475698159[/C][C]0.0248540951396317[/C][C]0.987572952430184[/C][/ROW]
[ROW][C]71[/C][C]0.0112647026061283[/C][C]0.0225294052122567[/C][C]0.988735297393872[/C][/ROW]
[ROW][C]72[/C][C]0.0159092412535880[/C][C]0.0318184825071761[/C][C]0.984090758746412[/C][/ROW]
[ROW][C]73[/C][C]0.0190027540052521[/C][C]0.0380055080105041[/C][C]0.980997245994748[/C][/ROW]
[ROW][C]74[/C][C]0.0355948856188701[/C][C]0.0711897712377403[/C][C]0.96440511438113[/C][/ROW]
[ROW][C]75[/C][C]0.0719784260414129[/C][C]0.143956852082826[/C][C]0.928021573958587[/C][/ROW]
[ROW][C]76[/C][C]0.0954055473460247[/C][C]0.190811094692049[/C][C]0.904594452653975[/C][/ROW]
[ROW][C]77[/C][C]0.0812768631290806[/C][C]0.162553726258161[/C][C]0.91872313687092[/C][/ROW]
[ROW][C]78[/C][C]0.0806513250489059[/C][C]0.161302650097812[/C][C]0.919348674951094[/C][/ROW]
[ROW][C]79[/C][C]0.0694525892260009[/C][C]0.138905178452002[/C][C]0.930547410774[/C][/ROW]
[ROW][C]80[/C][C]0.149023296788681[/C][C]0.298046593577363[/C][C]0.850976703211319[/C][/ROW]
[ROW][C]81[/C][C]0.145103111031310[/C][C]0.290206222062621[/C][C]0.85489688896869[/C][/ROW]
[ROW][C]82[/C][C]0.133457717515842[/C][C]0.266915435031684[/C][C]0.866542282484158[/C][/ROW]
[ROW][C]83[/C][C]0.118134441066346[/C][C]0.236268882132692[/C][C]0.881865558933654[/C][/ROW]
[ROW][C]84[/C][C]0.100212202109947[/C][C]0.200424404219895[/C][C]0.899787797890053[/C][/ROW]
[ROW][C]85[/C][C]0.0942278783622015[/C][C]0.188455756724403[/C][C]0.905772121637798[/C][/ROW]
[ROW][C]86[/C][C]0.127732037960140[/C][C]0.255464075920279[/C][C]0.87226796203986[/C][/ROW]
[ROW][C]87[/C][C]0.108773880648731[/C][C]0.217547761297462[/C][C]0.89122611935127[/C][/ROW]
[ROW][C]88[/C][C]0.0931874247068644[/C][C]0.186374849413729[/C][C]0.906812575293136[/C][/ROW]
[ROW][C]89[/C][C]0.079177807655544[/C][C]0.158355615311088[/C][C]0.920822192344456[/C][/ROW]
[ROW][C]90[/C][C]0.0783832195667967[/C][C]0.156766439133593[/C][C]0.921616780433203[/C][/ROW]
[ROW][C]91[/C][C]0.08567688928285[/C][C]0.1713537785657[/C][C]0.91432311071715[/C][/ROW]
[ROW][C]92[/C][C]0.134857888217041[/C][C]0.269715776434081[/C][C]0.86514211178296[/C][/ROW]
[ROW][C]93[/C][C]0.189727951085499[/C][C]0.379455902170998[/C][C]0.810272048914501[/C][/ROW]
[ROW][C]94[/C][C]0.185718436279667[/C][C]0.371436872559333[/C][C]0.814281563720333[/C][/ROW]
[ROW][C]95[/C][C]0.163634525903534[/C][C]0.327269051807069[/C][C]0.836365474096466[/C][/ROW]
[ROW][C]96[/C][C]0.142915442197670[/C][C]0.285830884395339[/C][C]0.85708455780233[/C][/ROW]
[ROW][C]97[/C][C]0.141177111799778[/C][C]0.282354223599556[/C][C]0.858822888200222[/C][/ROW]
[ROW][C]98[/C][C]0.123247910411754[/C][C]0.246495820823509[/C][C]0.876752089588246[/C][/ROW]
[ROW][C]99[/C][C]0.127482421153053[/C][C]0.254964842306106[/C][C]0.872517578846947[/C][/ROW]
[ROW][C]100[/C][C]0.109895929453535[/C][C]0.219791858907070[/C][C]0.890104070546465[/C][/ROW]
[ROW][C]101[/C][C]0.0970443435553982[/C][C]0.194088687110796[/C][C]0.902955656444602[/C][/ROW]
[ROW][C]102[/C][C]0.084296048347096[/C][C]0.168592096694192[/C][C]0.915703951652904[/C][/ROW]
[ROW][C]103[/C][C]0.0989025411737253[/C][C]0.197805082347451[/C][C]0.901097458826275[/C][/ROW]
[ROW][C]104[/C][C]0.125800585871633[/C][C]0.251601171743266[/C][C]0.874199414128367[/C][/ROW]
[ROW][C]105[/C][C]0.129536901572852[/C][C]0.259073803145704[/C][C]0.870463098427148[/C][/ROW]
[ROW][C]106[/C][C]0.114001830324503[/C][C]0.228003660649006[/C][C]0.885998169675497[/C][/ROW]
[ROW][C]107[/C][C]0.113203727600049[/C][C]0.226407455200098[/C][C]0.886796272399951[/C][/ROW]
[ROW][C]108[/C][C]0.103421448216989[/C][C]0.206842896433979[/C][C]0.89657855178301[/C][/ROW]
[ROW][C]109[/C][C]0.142950803748179[/C][C]0.285901607496359[/C][C]0.85704919625182[/C][/ROW]
[ROW][C]110[/C][C]0.125642333364629[/C][C]0.251284666729259[/C][C]0.87435766663537[/C][/ROW]
[ROW][C]111[/C][C]0.108630926973409[/C][C]0.217261853946818[/C][C]0.89136907302659[/C][/ROW]
[ROW][C]112[/C][C]0.199474675867114[/C][C]0.398949351734229[/C][C]0.800525324132886[/C][/ROW]
[ROW][C]113[/C][C]0.180819902653262[/C][C]0.361639805306523[/C][C]0.819180097346738[/C][/ROW]
[ROW][C]114[/C][C]0.180610023261218[/C][C]0.361220046522437[/C][C]0.819389976738782[/C][/ROW]
[ROW][C]115[/C][C]0.235242160780377[/C][C]0.470484321560754[/C][C]0.764757839219623[/C][/ROW]
[ROW][C]116[/C][C]0.309072719527449[/C][C]0.618145439054897[/C][C]0.690927280472551[/C][/ROW]
[ROW][C]117[/C][C]0.28370395925158[/C][C]0.56740791850316[/C][C]0.71629604074842[/C][/ROW]
[ROW][C]118[/C][C]0.255009695430292[/C][C]0.510019390860584[/C][C]0.744990304569708[/C][/ROW]
[ROW][C]119[/C][C]0.273141544882170[/C][C]0.546283089764339[/C][C]0.72685845511783[/C][/ROW]
[ROW][C]120[/C][C]0.367069827163176[/C][C]0.734139654326353[/C][C]0.632930172836824[/C][/ROW]
[ROW][C]121[/C][C]0.362386028431394[/C][C]0.724772056862787[/C][C]0.637613971568606[/C][/ROW]
[ROW][C]122[/C][C]0.342977245486136[/C][C]0.685954490972272[/C][C]0.657022754513864[/C][/ROW]
[ROW][C]123[/C][C]0.370494453981597[/C][C]0.740988907963195[/C][C]0.629505546018403[/C][/ROW]
[ROW][C]124[/C][C]0.340160362922689[/C][C]0.680320725845379[/C][C]0.65983963707731[/C][/ROW]
[ROW][C]125[/C][C]0.345279805027896[/C][C]0.690559610055792[/C][C]0.654720194972104[/C][/ROW]
[ROW][C]126[/C][C]0.317750174584018[/C][C]0.635500349168037[/C][C]0.682249825415982[/C][/ROW]
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[ROW][C]220[/C][C]0.589124250033732[/C][C]0.821751499932536[/C][C]0.410875749966268[/C][/ROW]
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[ROW][C]272[/C][C]0.703457459477989[/C][C]0.593085081044022[/C][C]0.296542540522011[/C][/ROW]
[ROW][C]273[/C][C]0.606001739919587[/C][C]0.787996520160826[/C][C]0.393998260080413[/C][/ROW]
[ROW][C]274[/C][C]0.530337366355995[/C][C]0.93932526728801[/C][C]0.469662633644005[/C][/ROW]
[ROW][C]275[/C][C]0.445618159039543[/C][C]0.891236318079087[/C][C]0.554381840960457[/C][/ROW]
[ROW][C]276[/C][C]0.629150952195323[/C][C]0.741698095609353[/C][C]0.370849047804677[/C][/ROW]
[ROW][C]277[/C][C]0.547323093204622[/C][C]0.905353813590756[/C][C]0.452676906795378[/C][/ROW]
[ROW][C]278[/C][C]0.392519142572311[/C][C]0.785038285144622[/C][C]0.607480857427689[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113583&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113583&T=5

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.6717187575269350.6565624849461310.328281242473066
110.5633497623837760.8733004752324480.436650237616224
120.5473512500608710.9052974998782580.452648749939129
130.4251835899122170.8503671798244340.574816410087783
140.4738189237051280.9476378474102560.526181076294872
150.5048159405565590.9903681188868820.495184059443441
160.404479091285550.80895818257110.59552090871445
170.3197367078599300.6394734157198590.68026329214007
180.3870079174958160.7740158349916310.612992082504184
190.4322358327933370.8644716655866740.567764167206663
200.3806731171790540.7613462343581080.619326882820946
210.315209025285750.63041805057150.68479097471425
220.3254070074416430.6508140148832870.674592992558357
230.2690557640201570.5381115280403150.730944235979843
240.2751232669666060.5502465339332110.724876733033394
250.2571338009450690.5142676018901380.742866199054931
260.3919169161058750.783833832211750.608083083894125
270.3429795234911960.6859590469823920.657020476508804
280.3117318584182190.6234637168364380.688268141581781
290.2664659701497860.5329319402995720.733534029850214
300.21601001602170.43202003204340.7839899839783
310.2026340501684550.405268100336910.797365949831545
320.1668790542744600.3337581085489200.83312094572554
330.1672011675705340.3344023351410680.832798832429466
340.156848465128520.313696930257040.84315153487148
350.1615936815887890.3231873631775780.838406318411211
360.1402629989261500.2805259978523010.85973700107385
370.1119845454655300.2239690909310600.88801545453447
380.08749021478108940.1749804295621790.91250978521891
390.07423163669025440.1484632733805090.925768363309746
400.05676701887749140.1135340377549830.943232981122509
410.04658137059934750.0931627411986950.953418629400652
420.0357150296784330.0714300593568660.964284970321567
430.03446982305072180.06893964610144370.965530176949278
440.02542489447549020.05084978895098030.97457510552451
450.07199031073521560.1439806214704310.928009689264784
460.05629930422916490.1125986084583300.943700695770835
470.06807693752643160.1361538750528630.931923062473568
480.05299308703945490.1059861740789100.947006912960545
490.05997682851434580.1199536570286920.940023171485654
500.05210894090550090.1042178818110020.9478910590945
510.05725109151957480.1145021830391500.942748908480425
520.05083643059403120.1016728611880620.949163569405969
530.03954725775955470.07909451551910950.960452742240445
540.03888174861233610.07776349722467220.961118251387664
550.03140386746843810.06280773493687630.968596132531562
560.02525423040021790.05050846080043580.974745769599782
570.02057883807485160.04115767614970320.979421161925148
580.01568532021102920.03137064042205840.98431467978897
590.01404896934585000.02809793869169990.98595103065415
600.01063187529661040.02126375059322070.98936812470339
610.01203382605824950.02406765211649910.98796617394175
620.009080412955267430.01816082591053490.990919587044733
630.006691321429388260.01338264285877650.993308678570612
640.005250490810310110.01050098162062020.99474950918969
650.006038453031810030.01207690606362010.99396154696819
660.005916212936705550.01183242587341110.994083787063294
670.004451445527746910.008902891055493830.995548554472253
680.00859053165558040.01718106331116080.99140946834442
690.01100135532718980.02200271065437970.98899864467281
700.01242704756981590.02485409513963170.987572952430184
710.01126470260612830.02252940521225670.988735297393872
720.01590924125358800.03181848250717610.984090758746412
730.01900275400525210.03800550801050410.980997245994748
740.03559488561887010.07118977123774030.96440511438113
750.07197842604141290.1439568520828260.928021573958587
760.09540554734602470.1908110946920490.904594452653975
770.08127686312908060.1625537262581610.91872313687092
780.08065132504890590.1613026500978120.919348674951094
790.06945258922600090.1389051784520020.930547410774
800.1490232967886810.2980465935773630.850976703211319
810.1451031110313100.2902062220626210.85489688896869
820.1334577175158420.2669154350316840.866542282484158
830.1181344410663460.2362688821326920.881865558933654
840.1002122021099470.2004244042198950.899787797890053
850.09422787836220150.1884557567244030.905772121637798
860.1277320379601400.2554640759202790.87226796203986
870.1087738806487310.2175477612974620.89122611935127
880.09318742470686440.1863748494137290.906812575293136
890.0791778076555440.1583556153110880.920822192344456
900.07838321956679670.1567664391335930.921616780433203
910.085676889282850.17135377856570.91432311071715
920.1348578882170410.2697157764340810.86514211178296
930.1897279510854990.3794559021709980.810272048914501
940.1857184362796670.3714368725593330.814281563720333
950.1636345259035340.3272690518070690.836365474096466
960.1429154421976700.2858308843953390.85708455780233
970.1411771117997780.2823542235995560.858822888200222
980.1232479104117540.2464958208235090.876752089588246
990.1274824211530530.2549648423061060.872517578846947
1000.1098959294535350.2197918589070700.890104070546465
1010.09704434355539820.1940886871107960.902955656444602
1020.0842960483470960.1685920966941920.915703951652904
1030.09890254117372530.1978050823474510.901097458826275
1040.1258005858716330.2516011717432660.874199414128367
1050.1295369015728520.2590738031457040.870463098427148
1060.1140018303245030.2280036606490060.885998169675497
1070.1132037276000490.2264074552000980.886796272399951
1080.1034214482169890.2068428964339790.89657855178301
1090.1429508037481790.2859016074963590.85704919625182
1100.1256423333646290.2512846667292590.87435766663537
1110.1086309269734090.2172618539468180.89136907302659
1120.1994746758671140.3989493517342290.800525324132886
1130.1808199026532620.3616398053065230.819180097346738
1140.1806100232612180.3612200465224370.819389976738782
1150.2352421607803770.4704843215607540.764757839219623
1160.3090727195274490.6181454390548970.690927280472551
1170.283703959251580.567407918503160.71629604074842
1180.2550096954302920.5100193908605840.744990304569708
1190.2731415448821700.5462830897643390.72685845511783
1200.3670698271631760.7341396543263530.632930172836824
1210.3623860284313940.7247720568627870.637613971568606
1220.3429772454861360.6859544909722720.657022754513864
1230.3704944539815970.7409889079631950.629505546018403
1240.3401603629226890.6803207258453790.65983963707731
1250.3452798050278960.6905596100557920.654720194972104
1260.3177501745840180.6355003491680370.682249825415982
1270.3014010529607270.6028021059214550.698598947039273
1280.2814115312518940.5628230625037890.718588468748106
1290.2551853080194290.5103706160388580.744814691980571
1300.2340555419788430.4681110839576850.765944458021157
1310.2105143521932740.4210287043865480.789485647806726
1320.1886231066358600.3772462132717200.81137689336414
1330.1901128083192950.3802256166385890.809887191680705
1340.2156204020408780.4312408040817560.784379597959122
1350.3931539239693390.7863078479386790.60684607603066
1360.3684504291753550.736900858350710.631549570824645
1370.3619317243084680.7238634486169360.638068275691532
1380.3311440416679730.6622880833359460.668855958332027
1390.3326034697586100.6652069395172210.66739653024139
1400.3038305992896280.6076611985792560.696169400710372
1410.3597266721583620.7194533443167240.640273327841638
1420.342659419174480.685318838348960.65734058082552
1430.582489780550790.835020438898420.41751021944921
1440.6359994570267850.7280010859464310.364000542973215
1450.7593012445571560.4813975108856880.240698755442844
1460.7374280467198760.5251439065602470.262571953280124
1470.7338309073244920.5323381853510170.266169092675508
1480.7307021144941750.538595771011650.269297885505825
1490.7299031190100260.5401937619799470.270096880989974
1500.7151829917110730.5696340165778540.284817008288927
1510.7277388620383270.5445222759233450.272261137961673
1520.7405301630245460.5189396739509080.259469836975454
1530.7371662776953930.5256674446092150.262833722304607
1540.736623745984080.5267525080318390.263376254015920
1550.732027538997050.53594492200590.26797246100295
1560.7084521429945640.5830957140108720.291547857005436
1570.7428948295812550.514210340837490.257105170418745
1580.7363991223799870.5272017552400270.263600877620013
1590.7378229281725990.5243541436548020.262177071827401
1600.7572287532611810.4855424934776370.242771246738819
1610.7643892449023280.4712215101953440.235610755097672
1620.8267630705980790.3464738588038420.173236929401921
1630.8162352657924580.3675294684150830.183764734207542
1640.7997007614895630.4005984770208750.200299238510437
1650.8244003970397150.351199205920570.175599602960285
1660.8446485725907410.3107028548185170.155351427409259
1670.8964364373506080.2071271252987840.103563562649392
1680.8962872439671490.2074255120657030.103712756032852
1690.8854928044248640.2290143911502720.114507195575136
1700.8731567961441990.2536864077116030.126843203855801
1710.9022411737297540.1955176525404910.0977588262702455
1720.9367231519748620.1265536960502760.063276848025138
1730.9330309549797010.1339380900405970.0669690450202985
1740.9239816080905480.1520367838189040.076018391909452
1750.9117118732191020.1765762535617960.0882881267808978
1760.8982874682790920.2034250634418150.101712531720908
1770.8879838467435210.2240323065129580.112016153256479
1780.8720878259051340.2558243481897320.127912174094866
1790.8690236426179380.2619527147641240.130976357382062
1800.8669247871584250.2661504256831510.133075212841575
1810.8747068218796410.2505863562407170.125293178120359
1820.8654867894847170.2690264210305660.134513210515283
1830.861677702808510.276644594382980.13832229719149
1840.846917090459570.3061658190808610.153082909540431
1850.8682651202219660.2634697595560680.131734879778034
1860.853154371055680.293691257888640.14684562894432
1870.8704908876831910.2590182246336180.129509112316809
1880.8721101426372610.2557797147254780.127889857362739
1890.8805305454591290.2389389090817430.119469454540871
1900.8634129928688080.2731740142623850.136587007131192
1910.8540625185627730.2918749628744530.145937481437227
1920.8325956232762280.3348087534475440.167404376723772
1930.826758326332840.3464833473343210.173241673667160
1940.8248064837595510.3503870324808980.175193516240449
1950.8285858592133840.3428282815732330.171414140786616
1960.8042800738484510.3914398523030980.195719926151549
1970.7892030542730010.4215938914539980.210796945726999
1980.7690534806808840.4618930386382330.230946519319116
1990.7489913466191760.5020173067616480.251008653380824
2000.7223547489954590.5552905020090830.277645251004541
2010.6918753992515210.6162492014969580.308124600748479
2020.6751552681739520.6496894636520960.324844731826048
2030.6624726274766380.6750547450467250.337527372523362
2040.635988039912760.728023920174480.36401196008724
2050.6042625877205520.7914748245588970.395737412279448
2060.5702028403424140.8595943193151710.429797159657586
2070.5332373212735370.9335253574529260.466762678726463
2080.6877817548752660.6244364902494670.312218245124734
2090.7721603375364360.4556793249271280.227839662463564
2100.741400929830790.5171981403384210.258599070169210
2110.7099793548762050.580041290247590.290020645123795
2120.7687820826339530.4624358347320940.231217917366047
2130.7453226926576930.5093546146846140.254677307342307
2140.723631337495080.5527373250098390.276368662504920
2150.690376526270450.61924694745910.30962347372955
2160.7286275427976180.5427449144047640.271372457202382
2170.6961746782888720.6076506434222550.303825321711128
2180.6610409430022340.6779181139955310.338959056997766
2190.6279202777122340.7441594445755320.372079722287766
2200.5891242500337320.8217514999325360.410875749966268
2210.6702232742204160.6595534515591680.329776725779584
2220.6328156430249540.7343687139500910.367184356975046
2230.5947272397089240.8105455205821530.405272760291076
2240.5544467601829760.8911064796340490.445553239817024
2250.5231286534779640.9537426930440720.476871346522036
2260.5165566738715580.9668866522568840.483443326128442
2270.6144470129748740.7711059740502520.385552987025126
2280.5751467503792570.8497064992414860.424853249620743
2290.6264141186505290.7471717626989420.373585881349471
2300.5883829555805820.8232340888388370.411617044419418
2310.5757963884125020.8484072231749960.424203611587498
2320.5558145580032540.8883708839934920.444185441996746
2330.7421820718886840.5156358562226320.257817928111316
2340.7054025336073650.589194932785270.294597466392635
2350.755666289325120.4886674213497620.244333710674881
2360.742384690798980.5152306184020410.257615309201021
2370.7049204167160480.5901591665679030.295079583283952
2380.6737847940909430.6524304118181130.326215205909057
2390.64337224797260.71325550405480.3566277520274
2400.6787131455501820.6425737088996360.321286854449818
2410.6570475317638170.6859049364723660.342952468236183
2420.6237867293318780.7524265413362440.376213270668122
2430.6318061401488620.7363877197022750.368193859851138
2440.733249304122450.5335013917550990.266750695877549
2450.7247891754008540.5504216491982910.275210824599146
2460.6796396230678380.6407207538643250.320360376932162
2470.6312706235248040.7374587529503930.368729376475196
2480.5937365682012950.812526863597410.406263431798705
2490.5618586072737320.8762827854525360.438141392726268
2500.5131291830774590.9737416338450820.486870816922541
2510.4727336050670910.9454672101341830.527266394932909
2520.4195035685269870.8390071370539750.580496431473013
2530.3705428775662410.7410857551324830.629457122433759
2540.3504502149261650.700900429852330.649549785073835
2550.2997261962018520.5994523924037040.700273803798148
2560.4092567870750110.8185135741500220.590743212924989
2570.3781753772722450.756350754544490.621824622727755
2580.3318035751116510.6636071502233020.668196424888349
2590.3353984627948480.6707969255896970.664601537205152
2600.3195776332140430.6391552664280860.680422366785957
2610.304496481899310.608992963798620.69550351810069
2620.2856770358058280.5713540716116550.714322964194172
2630.2975964888280740.5951929776561480.702403511171926
2640.3457054530600860.6914109061201730.654294546939914
2650.2964378235691510.5928756471383030.703562176430849
2660.4387659840479170.8775319680958350.561234015952083
2670.6791573507053240.6416852985893530.320842649294676
2680.6111033713223690.7777932573552630.388896628677631
2690.5342773926853410.9314452146293180.465722607314659
2700.4661670530508280.9323341061016560.533832946949172
2710.4274345305297170.8548690610594340.572565469470283
2720.7034574594779890.5930850810440220.296542540522011
2730.6060017399195870.7879965201608260.393998260080413
2740.5303373663559950.939325267288010.469662633644005
2750.4456181590395430.8912363180790870.554381840960457
2760.6291509521953230.7416980956093530.370849047804677
2770.5473230932046220.9053538135907560.452676906795378
2780.3925191425723110.7850382851446220.607480857427689






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level10.00371747211895911OK
5% type I error level170.0631970260223048NOK
10% type I error level260.0966542750929368OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 1 & 0.00371747211895911 & OK \tabularnewline
5% type I error level & 17 & 0.0631970260223048 & NOK \tabularnewline
10% type I error level & 26 & 0.0966542750929368 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113583&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]1[/C][C]0.00371747211895911[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]17[/C][C]0.0631970260223048[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]26[/C][C]0.0966542750929368[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113583&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113583&T=6

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Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level10.00371747211895911OK
5% type I error level170.0631970260223048NOK
10% type I error level260.0966542750929368OK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}